News & Views


Founded and Funded: Starting a Company with your Best Friend, the co-founders of Algorithmia, Kenny and Diego

(Kenny Daniel and Diego Oppenheimer)

Tim Porter opens Season Two of Founded and Funded, with Algorithmia’s founders, Kenny Daniel and Diego Oppenheimer.  This duo started Algorithmia in 2014 and teamed up with Madrona, working out of our office for a while as they got off the ground.  The team has made huge strides since their initial algorithm marketplace.  Corporations and government institutions now turn to Algorithmia  to enable them deploy AI models and run them at scale.

Kenny and Diego met in college at Carnegie Mellon and stayed in touch as they went very different directions – Kenny to do a PhD and Diego into business at Microsoft.  They came back together to bring the power of academia to business and started the company to unlock the power of algorithms.

They talk about everything from the six month backpacking trip with a beat up laptop that was the genesis of the company to building a distributed team (by happenstance) to where we are in the adoption of machine learning and intelligent applications in this wave of innovation.


Also available on all your favorite podcast platforms.

POSTED IN: Madrona News

Building a B2B Marketing Culture from the Ground Up with Elissa Fink, former CMO of Tableau Software

The latest Founded and Funded podcast with with Madrona Venture Group’s Tim Porter

Elissa Fink joined Tableau early in the company’s journey as their marketing lead.  Tableau was always a product driven company with an early passionate audience.  Elissa saw this and undertook at the start of her Tableau career to update the brand positioning to be people first and lead with their stories.

Tableau is one of the Seattle success stories.  It was acquired by Salesforce for $15.7 billion in the summer of 2019, making it the second largest acquisition ever in the Seattle tech ecosystem and brought together the leader in CRM with the leader in analytics.  The company started in 2003 and Elissa joined Tableau four years later when revenue was under $5 million a year.  She helped grow the company to over $1billion in annual revenue and helped take the company public. 

A key to Tableau’s marketing success was an intense focus on customers and end users.  By tapping into these early customers and their appreciation of getting a job done faster and better, Tableau was able to have early broad-reach success that was later leveraged into larger enterprise sales.

Elissa addresses the importance of brand in the early days.

“It’s all about consistency.”

– Elissa Fink

The brand voice was the backbone for the demand generation work which was the key to the growth of the young company.

As the company moved into enterprise sales, marketing played a big role.  Elissa and her team had seen the writing on the wall and been working with the influential analyst firm, Gartner, for some time.  Elissa remembers when the Magic Quadrant that had them clearly in the challenger category was sent to her – that was a big day for the company.

In fact one of the important roles for marketing is to look 18-24 months ahead.  What will the market want at that time?

Competition was sparse in the early days but that changed.  Microsoft announced a competing product and wrapped it into their formidable enterprise sales process.  This was a frightening time at Tableau but the strength of the product prevailed.  Customers who were passionate about data wanted to use Tableau and they continued to buy.  Tableau’s product driven approach paid off yet again.

For startup companies, Elissa knows hiring is hard.  For marketing which has become such an analytics and numbers focused endeavor, Elissa advises not to hire for experience but hire people who are deeply interested in a problem you need to solve, and who have the good judgement needed to succeed in a startup.

For marketing leads, she suggests assessing the assets you have across brand, product, and community.  Where are the leverage points? And where do you need to shore up your leverage points in order to have a strong basis for marketing.  This assessment will help you prioritize in the busy world of a startup.

Elissa is an advisor to startups including, Qumulo and Amperity and sits on the board of the Washington Technology Industry Association.  She recently taught a class at the University of Washington on B2B marketing.

Note: The largest acquisition was Amgen’s acquisition of Immunex for $16.0B in 2002. Source:

POSTED IN: Madrona News

Our Investment in Clari, Intelligent Tools for the CRO

We, at Madrona Venture Group, are excited to invest in Clari, a company applying AI to the multi-layered task of revenue operations.

Earlier this summer, we raised the first Madrona Acceleration Fund and Clari is the first investment out of that fund. The fund’s focus is to invest in great companies and teams that have found product-market fit and are ready to scale to the next level. Clari already has had incredible success and is on that path.

Over the last year or so, we have focused deeply on a number of themes that have guided our investment activities.  One such theme is intelligent applications. Clari is a great example of an intelligent application that ingests data from a variety of sources (CRM systems, marketing tools, customer success tools, email, calendar and the like) and applies AI and ML techniques to provide better insights and forecasting capabilities to drive revenue operations for an enterprise.

We believe there are some key trends in the industry which make a platform tool such as Clari a “must have” solution for all Go-To Market (GTM) employees in an enterprise today.  These trends include:

  • Companies continue to rapidly innovate on business models. Driven by changes in customer behavior, over the last decade we have seen a strong movement from traditional license models to subscription models.  And we are in the early days of moving from subscription models to consumption models.  As these business model innovations continue, the challenges that businesses and organizations and people deal with are getting more complex.
  • The rise of the CRO (Chief Revenue Officer). More and more enterprises are looking to have a top-level leader who looks holistically at all aspects of revenue operations.  This has started shining the spotlight on and the opportunity to manage revenue generation as a predictable end-to-end business process and managing  marketing, sales and customer success as one integrated system as opposed to different silos.
  • ML and AI technology advances have truly enabled every application that is being built today to be an intelligent application. Being able to bring data together from multiple sources and build a continuous learning system that provides better insights and predictive capabilities is becoming more possible today than ever before.

Clari is an AI and ML platform that looks holistically at revenue operations by unifying sales, marketing and customer success systems and data to provide insights and forecasting capabilities. It is led by a fantastic team including Andy Byrne (CEO and Co-Founder) and Venkat Rangan (CTO and Co-Founder) who have a long history of working together in a variety of successful start-ups over a couple of decades and they bring a tremendous amount of experience and expertise to solving this problem in a best-in-class way for all businesses.

We heard amazing feedback from Clari’s customers about why they love the product.  Hearing things like “sales folks just love the product”, “my CEO doesn’t ask me for forecast information anymore and just looks at Clari’s forecast”, “my Board member’s first question always on the plan is how does this relate to Clari’s forecast”, etc. reinforce how Clari’s core value proposition resonates strongly with customers.

For these reasons, we are thrilled at the opportunity to invest in Clari and to be a valuable partner in the journey as we build the next generation AI-driven revenue operations platform for companies around the world.


POSTED IN: Madrona News

Building Marketplaces is Hard, Mark Britton Shares His Tips for How to Succeed

Seattle is known for marketplaces, Expedia, Amazon, Zillow, Redfin, Rover.

“Building them is REALLY hard.”

If you are looking to build a marketplace based company – you inherently have two sides and two potential customer groups for whom to optimize.  In the latest episode of Madrona’s podcast, Founded and Funded, Mark Britton, the founder of AVVO, talks about how he approached this at AVVO; the opportunities founders have to create meaningful marketplaces and the common mistakes they make.

One of these mistakes comes from misjudging who your most important customer is.

“The touchstone is the consumer – you have to really understand the consumer and solve their problem in a very unique way.”

Since a marketplace is a flywheel, you need to get it going and that is not easy.  Mark suggests get started by limiting your geography or the product in a way that makes it possible to generate the supply side in a meaningful way for your very first customers.  For AVVO that meant a practice area of law and a geographic region.

With most marketplace businesses, the big tech companies will start to encroach.  One example is the Trips service from Google released earlier this year that offers a search for vacation packages, flights and more, all of which have been traditional fare for travel marketplaces for years.

“Every single e-commerce model that is informationally driven; Google believes they should own that.”

Mark suggests that entrepreneurs who are thinking about a building a marketplace, focus on the community they have a passion for.  Google is trying to capture everything about the world, you know a community or a specific market, so leverage that focus and lean into it.

Build out the tools to increase interactivity on the platform and keep your eyes open for when the competition from big tech companies heats up.  Your focus has the opportunity to prevail against big tech.

The addition of AI and ML related technologies is another challenge for startup marketplaces – the big companies have teams, compute and the technology to help make the connections and matches in a marketplace.  Even if they do so incrementally, they will be doing it at scale.

This all comes back to your unique love of the community and ability to understand and build it in a way that is not possible from a Google or an Amazon.

“Building community is such an art – Google will not be your tight community.”



Mark is a Strategic Director at Madrona Venture Group and Elisa La Cava is a Senior Associate.  You can contact them by emailing or connecting through LinkedIn



POSTED IN: Madrona News

Founded and Funded – Building a Customer Satisfaction Team (and a lot more) with Oliver Sharp

In this episode of Founded and Funded, Tim Porter, speaks with Oliver Sharp, co-founder of Highspot about the journey of building the company.  They talk about the inspiration behind Highspot (corporate content you need for your job should be as easy to find as a how to YouTube video), building a culture of customer satisfaction from day one, and how people from large companies transition (or don’t transition) to startup life.

Highspot has raised $120 million with their most recent round of $60 million announced in June of 2019.  Highspot is a sales enablement platform that helps sales people find the content they need to close deals.

The team came together at Microsoft and the transition to a startup was a return to their roots as hands on learners.  Though senior contributors and managers at Microsoft, as Oliver says “a startup doesn’t care how senior you are – you have to learn it all yourself” and they all had to re-learn the hands on work of creating and marketing a product. Customers were at the center of this.

Some lessons from this discussion:

  • Customers have crucial insight, though you have to figure out which ones to pay attention to early on.  Oliver talks about how they learned more from the customers who passed than the ones who bought the product in the very early days.  The ones who passed had reasons they didn’t and understanding those were key to building the product.
  • But while focusing on the product is crucial it’s not the way you succeed.  You have to take your technological masterpiece and tune it to the customers’ needs.
  • And the words are important – How you define the problem may not be how they define it.  Highspot originally set out to create the best content search out there to help marketers and sales people identify the best content for a given situation.  But your customers “don’t think about search problems, they think about the making more money problem.”
  • So you both need a great product and you need the story you are telling your customer to fit with what they are looking for, or the pain they are feeling.  You aren’t selling search (in this case) you are selling the solution to their problem (which you know is mostly search.).
  • CSAT or Customer Satisfaction measurement is not a new thing in business but with SaaS it is more tightly woven into the software renewal cycle.  And it’s so much easier to measure and to react quickly.  SaaS puts more emphasis on the customer satisfaction as a direct ingredient in sales.
  • Building a successful CSat team starts with the product creators. Start with the people who helped design the product.  Those people are the most invested in what the product is now – hearing from customers is the most powerful way to learn where you went wrong.
  • Other topics of interest are building a team from junior on up – how hiring college grads has worked out extremely well for HIghSpot – and Oliver covers what not to say in a startup interview!

You can listen here or on any of the platforms you prefer – iTunes, Spotify, Google Play, SoundCloud, and Stitcher

POSTED IN: Madrona News

Teamwork from Sports to Business

Teamwork is what enables startups to survive to be successful companies. Building a team takes all kinds of people, coaches, players, business experts and investors. Today Terry Myerson  and S. Somasegar from Madrona and many others including Satya Nadella, Russell Wilson, Ciara, Ben Haggerty (Macklemore), Amy Hood and others stepped up to invest in a great Seattle community builder – the Seattle Sounders. There are a lot of fans here  and we are excited to support the team and the organization through our spirit! Here is Terry’s story of how it came about.

POSTED IN: Madrona News

Founded and Funded Episode 1 – Hope Cochran on the Entrepreneurial Journey – Hers!

Our first podcast is live – Hope Cochran shares her stories of startup life  – mistakes made and lessons learned in conversation with Principal, Daniel Li.  It was a great conversation and we hope you like it! You can also find this in iTunes, Spotify and SoundCloud with Google Play coming very soon.

POSTED IN: Madrona News

Founded and Funded – Madrona’s Podcast about Startup Life

Today we are launching a podcast.  We looked around at the offerings for startups in Seattle and felt there was room for experienced entrepreneurs to share their moments of truth – where they made mistakes and figured it out, a turning point in the business, their “ah ha” moment, or just what got them through.  And to tell some great stories along the way.    We have entrepreneurs of all kinds in and out of our doors every day and every one of them has an interesting story.  We hope to share some of them here.

In each episode, someone from the Madrona team will sit down for a discussion with one of these entrepreneurs.  We hope you get to know the broader team here through some of these discussions – from investors to HR and recruiters to Biz dev and Comms pros.  In the first season you will hear from Managing Director Hope Cochran who used her pursuit of opera early in her career to help her manage a room full of businessmen, and Venture Partner, Mark Britton on what he learned building Avvo into a leader in the field.  Others in the first season are Oliver Sharp, founder of HighSpot who advocates that customer success is not just a department at a company, it’s everyone’s number one goal, and Elissa Fink who talks about how building a BtB brand that resonates with customers is just as important as a BtoC brand.

We worked with Larj Media to get going and they were great Mentors – thanks Tina and Joelle!

Here is the teaser to give you an idea of what to expect. We will be putting the podcast in all the usual places, ITunes, Spotify, Google Play, SoundCloud etc – if there is somewhere you want it and can’t find it let us know at foundedandfunded(Replace this parenthesis with the @ sign)

POSTED IN: Madrona News

It’s Been an Incredible Experience – 23 years on the Amazon Board

Managing Director, Tom Alberg, announced today that after 23 years on the board of he intends to step down in May of 2019.  Alberg first invested in in the company’s Series A financing in 1995 and is the longest serving member of the board after CEO and founder, Jeff Bezos.  Alberg will continue as a managing director of Madrona Venture Group and several corporate and non-profit boards.

“Serving on the Amazon board has been an incredible experience.    Amazon’s growth and expansion is a testament to not only how technologies like the Internet have expanded in just 20 years to dominate our lives, but also to the ability of Jeff to build a team that inspires innovation and creativity at every turn,” commented Alberg.

Alberg is a co-founder and managing director at Madrona Venture Group, which invests in information technology companies in the Seattle region with a focus on early stages companies.  The firm raised its 7th fund last year and has nearly $1.6 billion under management. Alberg also serves on the board of Impinj (NASDAQ:PI) and the non profit boards of Oxbow Farm & Conservation Center, the Pacific Science Center and  Alberg and his wife, Judi Beck, cofounded Oxbow as well as the Novelty Hill Winery.

The original Amazon board was Jeff Bezos, Tom Alberg and John Doerr of Kleiner Perkins.  Doerr left the board in 2010. While the board has grown over the years, the company and Alberg maintained a philosophy of having a balance of business know how and people who are on the cutting edge of technology.

“Being a venture capitalist in one of the healthiest tech ecosystems in the U.S. means that I get a bird’s eye view into the latest trends driving both startups and customer traction.  Having this balance on the board for a company like Amazon has been very helpful for the company’s growth,” added Alberg.

Madrona has created strong ties with Seattle anchors, Amazon and Microsoft.  The firm holds regular briefings with both companies in key technology areas such as cloud, productivity and new user interfaces such as voice.  This connectivity in an increasingly competitive world is helpful for entrepreneurs of early and mid stage companies.





POSTED IN: Madrona News

The Big Clouds are All “Hybrid Clouds” Now!

First it was Azure stack, then came AWS/VMWare with AWS Outpost and now there is Google Anthos.  Google announced general availability of its Anthos Cloud Services Platform at Google Next this week.  Anthos has many elements but the telling one is that it lets you run Google Cloud on-premise and in other cloud environments.

As the number three provider with a new energized leader, you have to wonder if it’s too little, too late?   Time will tell.  What is interesting is that this move toward hybrid reflects what we are seeing in enterprise use of public clouds – they are all in as long as it’s hybrid.  And increasingly multi-cloud.

While each of these offerings from the cloud providers is different, the unifying theme of the Anthos announcement is that the large public clouds are fully embracing the reality of the enterprise hybrid cloud.

So, what exactly does “hybrid cloud” mean?  In short, it means that portions of an application or workload can run in your “on premise” data center while other portions run in a public cloud data center.  This combination of public and private cloud infrastructure helps optimize the agility, cost, latency, and performance of workloads while minimizing the additional security and manageability requirements.  It is especially helpful for existing apps that can move a portion of the overall workload (say storage backup or compute “bursting”) to the cloud.  And, it is even better for new or existing applications that want to build or modernize workloads in a cloud native manner.

One way to do this is to have infrastructure on premise that looks and acts like the public cloud’s Infrastructure As A Services (IAAS) offered today by AWS or Azure.  AWS Outpost and Microsoft’s Azure Stack are services that help in these use cases.  Another approach is when you are trying to move or migrate portions of your application to the public cloud. This is what Google Anthos is all about

Why is Google doing this?  First, they hope to compel you to modernize your infrastructure by embracing a lightweight virtualization technology called containers that are predominantly orchestrated/managed by a service called Kubernetes that was originally created at Google.  The second reason is that once your application runs in containers it is more portable from one cloud (public or private) to another cloud.  In this way, Google hopes to move applications off of AWS and Azure.  Here is how the VentureBeat put it:

“It’s one thing to use a service like this for new applications, but many enterprises already have plenty of line-of-business tools that they would like to bring to the cloud as well. For them, Google is launching the first beta of Anthos Migrate today. This service will auto-migrate VMs from on-premises or other clouds into containers in the Google Kubernetes Engine.”

Being in a distant 3rd place position can lead to a counterintuitive strategy.  And, Google could benefit from leading the efforts to make workloads portable in the cloud (both to move them from on premise to Google and to move them from AWS/Azure to Google).  But, they will have competition in leading the containerization charge from VMWare, Redhat/IBM and in some forms the market leading clouds!


POSTED IN: Madrona News

Quantum Computing is Coming, Let’s Focus on Getting our Computer Science Workforce Ready
(Photo credit: Andrea Starr/Pacific Northwest National Laboratory – Derek Kilmer, Tom Alberg)

At Madrona, we are investigating the potential for quantum startups, taking quantum dives with Craig Mundie and spending off-sites delving into the state of the technology with expert researchers.  We are excited about this area and are continuing to meet with companies venturing into this exciting area of computation.  This post was first published by Geekwire.  

This week I had the opportunity to speak at the Northwest Quantum Nexus Summit, co-sponsored by Microsoft, the University of Washington and Pacific Northwest National Labs.  The Summit brought together, for the first time, the large network of quantum researchers, universities and technology companies working in Quantum Information Science (QIS) in our region to share quantum developments and to work together to establish the Pacific Northwest as one of the leading quantum science centers in the world.

Quantum computing has the potential to transform our economies and lives.  As one of the Summit speakers said, we are on the “cusp of a quantum century.”  Quantum computers will be able to solve problems that classical computers can’t solve, even if they run their algorithms for thousands of years. Quantum computers are not limited to the on-or-off (one-or-zero) bits of today’s digital computers. Quantum computers manipulate “qubits” that can be one-and-zero simultaneously which allows exponentially faster calculations.

Quantum computers are expected to be able to crack present day security codes, which is already causing scientists to work on devising new encryption protocols to protect consumer and business data and national security.

Applications developed for quantum computers likely will help us overcome existing challenges in material, chemical and environmental sciences such as devising new ways for sequestering carbon and improving batteries.

Even though the Seattle area is one of the top two technology centers in the U.S., along with the San Francisco Bay area, we have to make investments now to ensure we become a leading quantum center.  To achieve this goal, I argued that we will need to substantially increase financial support to build up the UW’s quantum research capacity and equally important, to create an extensive quantum information science curriculum.   The UW’s School of Computer Science and Engineering began this year to offer a course teaching Microsoft’s Q# language, but one course is not enough if we are to make our area one of the major quantum centers of the future.

Fortunately for our region, Microsoft is one of the acknowledged leaders in quantum computing and is committed to building our regional network.  CEO Satya Nadella gives credit to former Microsoft chief technology and research leader Craig Mundie for launching Microsoft’s quantum initiative 10 years ago.

Microsoft’s goal is no less than to build a “general-purpose” quantum computer – the holy grail of quantum computing.  In the meantime, they are supporting efforts to build a cadre of researchers who are familiar with quantum and capable of writing quantum programs.  They have developed and launched a quantum computer language, Q# (Q Sharp), a quantum development kit and “Katas,” which are computing tasks, that classical computer scientists can use to learn quantum computing skills.  They are also building an open source library of quantum programs and have launched the Microsoft Quantum Network to provide assistance to quantum startups and developers.

The federal government has recently launched the National Quantum Initiative which will provide $1.2 billion over the next five years primarily to quantum researchers.  The President signed the new law in December after the bill was approved by unanimous consent in the Senate and a vote of 348-11 vote in the House.  Among the purposes are to build a “quantum-smart workforce of the future and engage with government, academic and private-sector leaders to advance QIS.”

This federal funding is welcome, even though less than required for a Manhattan-style project equivalent to China’s national quantum initiative. It will be highly important to our region that our Congressional delegation, several members of whom are particularly tech savvy, advocate our case for a fair share of this funding.  Our Washington legislature should support this by making appropriations for quantum computing and education at the UW as a down payment showing local support.

There is also a role for private companies to support our quantum efforts beyond what Microsoft is already doing.  I am reminded of the grants by Amazon to the UW in 2012 during the Great Recession engineered by then UW CSE Chair Ed Lazowska to recruit two leading professors, Carlos Guestrin from Carnegie Mellon and Emily Fox from the University of Pennsylvania, to strengthen the UW’s machine learning expertise.  The two $1 million gifts created two endowed professorships.  Inflation has certainly raised the price for endowed professorships, but perhaps this could be repeated.  Another way to build our region’s quantum expertise would be for a local tech entrepreneur to follow the example of Paul Allen who endowed five $100 million plus scientific institutes, one of which is the Allen Institute of Artificial Intelligence, headed by former UW professor and currently Venture Partner at Madrona, Oren Etzioni.

Building a quantum workforce begins in K-12 schools with teaching computer science, which is a stepping stone to quantum information science.  K-12 schools in the U.S. are woefully deficient in teaching basic computer science.  Nationally, only 35% of high schools offer a computer science course, according to  And in low income and minority schools this is even lower since the 35% reflects a lot of suburban schools which are more likely to offer computer science courses.

Nationally, only 35% of high schools offer a computer science course, according to

We are beginning to address this gap in high schools but a much larger commitment is needed.  Private companies can help fill part of the gap.  Amazon recently announced its Future Engineers program, which includes a $50 million investment in computer science and STEM education for underprivileged students.  As part of this program, a few weeks ago, Amazon announced  grants to more than 1,000 schools in all 50 states, over 700 of which are Title 1 schools.  Studies have shown that if a disadvantaged student takes an advanced computer science course in high school, they are eight times as likely to major in computer science at a university.

In addition to Amazon, Microsoft and other tech companies have programs to increase the teaching of computer science.  One of those programs, backed by Microsoft, is TEALS, which organizes employees and retired employees as volunteers to teach computer science in schools.  Amazon, Microsoft, and other tech companies are big financial supporters of which is having a significant effect on increasing the teaching of computer science in public schools.

The Bureau of Labor Statistics projects that by 2020 there will be 1.4 million computer science related jobs needing to be filled but only 400,000 computer science graduates with the skills to apply for those jobs.  Only a tiny percentage of the 400,000 are minorities or from low income families.  A similar gap exists in Washington State, with a gap of several thousand between the jobs needing to be filled and the number of annual graduates.

In Seattle and other tech centers in the U.S., we have been fortunate that we have been able to attract and retain a very substantial number of computer scientists from other countries to fill these jobs.  But with immigration and trade uncertainties, this flow is uncertain and may not be as robust as needed.  Even more important, by not providing the opportunity for our kids, particularly disadvantaged children, we are short-changing them.  The best way to close the income gap is to improve our public educational system so a broader segment of our population can qualify for the jobs of the future. Organizations such as the Technology Access Foundation are attacking this problem head on by creating curriculum, recruiting minority teachers and building schools.  We need to support these organizations and implement their approach broadly.The best way to close the income gap is to improve our public educational system so a broader segment of our population can qualify for the jobs of the future.

The best way to close the income gap is to improve our public educational system so a broader segment of our population can qualify for the jobs of the future.

At the university level, we are also deficient in educating a sufficient number of computer scientists.  Even at universities such as the UW, with large and high quality computer science schools, we are unable to fill the demand for computer scientists.  The Allen School graduates about 450 undergraduate students annually.  Although this is double what the school produced a few years ago, it is woefully short of the several thousand needed annually in our state.  This needs to be doubled again but funding is lacking.

In short, our region needs to recommit to building our computer science workforce beginning in our K-12 schools and undertake a new effort to build our quantum expertise and workforce.

POSTED IN: Madrona News

All About Your Board of Directors

Pictured Forest, Alan and Len

Last week, Create33 hosted a panel for startups on The Board of Directors – how to manage, form, and think about them in the company building process.  Len Jordan, managing director at Madrona, Forest Key, founder and CEO of Pixvana and Alan Smith of Fenwick & West talked about good and bad board experiences and gave some top tips for getting started and staying on an even keel.

What is the purpose of a board for a startup founder/company?

Everyone agreed that the board is a resource for a founder to leverage and one they can’t afford to ignore.  Board members are there to help you build your business by bringing knowledge, experience, relationships and perspective you as a founder may not have.  This means you need to choose your board members wisely.  Look for people who can work well in groups, are prepared to dig in and spend the time and who have skills and experiences you don’t.

How early is too early to start a board? Never too early.

But there are some considerations:

Size  In the early (pre-A series) stage, your board should be small –  you, an angel investor, an independent advisor with strong business and domain expertise –  would be a good size.  You have to keep in mind that as you add investors in venture rounds, those investments usually come with a board seat.  And if the board gets too big, it’s not that useful.  It’s hard to have great conversations with big groups – and that’s what having a board is all about.  Getting into hard problems, looking ahead and coming up with steps for growth.  Amazon, the largest market cap company in the US (most days) has 10 people on their board.  Also beware of too many board observers.  Observers are in the room but don’t vote.

Advisory Board vs Board of Directors: What is the difference?  Governance and scope of engagement are the main differences.   Many companies have both types of boards.  Advisors often have specific domain expertise that is useful but are not necessarily company builder types.  Advisory board members should be set up to serve a set amount of time and then, if you pivot your business and that advisory board member doesn’t make sense for your business, there is a pre-arranged way to say goodbye.  There was also a thread about changing out independent board members or advisory board members. It’s never easy – the advice was to make sure you set up the compensation and board member agreement ahead of time so it’s clear what the steps are for all involved.  And, as with any type of management situation, stay very connected and transparent in your communication.  For your venture investors, it is very rare for a firm to trade out board members, and they are usually on your board for the long haul.  Pick your investors carefully, do as much diligence on the partner as they do on your company and test-drive independent directors as advisors first to get to know them and understand their value-add and chemistry with your team.

Why have a board so early?

Building a company is a group process, especially once you take outside capital and bring investors onto your board who now have a very vested interest in your success.  Founders and companies who don’t have the motion of spending time looking outside of the company for insight into problems and solutions can run into problems.  Venture investors at early stages are looking to partner and seeing the founder be forward thinking about running his or her business shows that there is a fit.

What is appropriate compensation for board members?

Investor board members generally do not receive compensation from the company but independent board members and advisory board members need to be compensated.  You would want to draw up agreements for each of these members that outlines the payment and vesting schedule – and puts some time limits in place for re-evaluation.  Typical compensation is a standard stock option grant in a range between .25-.5% of outstanding equity.  The amount should be the same for every director.

How do you choose board members?

When you think about your board – they will likely be with you for 10-15 years so you should think carefully about who those people are. This is also an important step in taking venture financing. You get money and assistance from a firm, but the partner is the one you will spend the most time with.  Get to know him/her and how they think before you go down that road.

For independent board members, the panel urged that founders think about choosing people with experiences different from your own. Your mentor at your old job is not a good fit – they shared that information with you already. That person is a friend and you can get advice for free from them without complicating things.

How do you run board meetings?

This starts before the board meeting. The group was unanimously in agreement that the board presentation should be sent around ahead of time (2-3 days) and you should expect that everyone will have read it ahead of time.  This means you can zero in on opportunities and challenges that you, your exec team and board members want to address (you should ask ahead if things stand out to them) and also use the time creatively to address bigger strategic questions/alternatives and tradeoffs you face.

How do you work with your board outside of board meetings?

Early and often was the advice on this!  Regular communication with board members is highly encouraged.  Send weekly or monthly updates (depending on size and your inclination) and don’t hide the bad news.  Put that upfront and be transparent.  Meet with board members outside of the board meeting 1:1 – that is where good ideas come up and you can more easily discuss challenges.  There were examples of a biweekly coffee with a director, a Sunday evening email that summarizes the week prior and pre-meetings with board members ahead of a monthly or quarterly meeting. One person said they usually send out 4-5 topics that could be discussed at a board meeting to see what board members are interested in.

Regular communication with board members is highly encouraged.  Send weekly or monthly updates (depending on size and your inclination) and don’t hide the bad news.  Put that upfront and be transparent.

Who from your company should be in a board meeting?

Remember the size discussion above? Keep that in mind but know that your board needs to hear from leaders in the company – they might want to meet with them 1:1 too. Pull the right people in to discuss issues and present their areas of the business – it’s great for your internal team to know the external team.

  • For more on this check out Len Jordan’s (timeless) TechCrunch post – just don’t comment on the photo’s role in the timeless comment!
  • For more events at Create33 – sign up to receive their newsletter!

Alan Smith is chair of Fenwick & West’s corporate practice. The firm provides comprehensive legal services to leading technology and life sciences companies — at every stage of their lifecycle — and the investors that partner with them.

 Forest Key is founder and CEO of Pixvana. Pixvana, a virtual reality solutions provider, helps enterprises develop cutting-edge approaches to solve business challenges in innovative ways. The company is venture-backed by Vulcan Capital, Madrona Venture Group, Microsoft, Cisco, Raine and Hearst Ventures.

Len Jordan is a managing director at Madrona Venture Group, an early stage venture firm investing in information technology with a regional focus on Seattle.  The firm has with nearly $1.6 billion under management. 



POSTED IN: Madrona News

Standing Ovation – Cloud Based Clinical Informatics

Pictured l-r S. Somasegar, Ted Kummert, Chris Picardo, Barry Wark (seated) Winston Brasor

We are excited to announce today our investment in, a company that is building the next-generation suite of cloud-based clinical informatics tools for the genomic and molecular testing industry. The company was founded by Barry Wark and Winston Brasor, building off of software that Barry originally built while a graduate student at the University of Washington in Seattle. Ovation’s mission is to provide modern tools to molecular testing labs, allowing them to automate their operations and workflow while simultaneously unlocking the opportunity within their data.

For the past couple years, Madrona has been thinking deeply about the intersection of the life sciences and computer science. We believe that there is a significant amount of innovation waiting to be realized when modern cloud infrastructure and data analytics capabilities meet the vast amount of data and research within the life science and biotech industries. In parallel, significant innovation in the speed and cost of genome sequencing technology has allowed researchers to acquire vast amounts of valuable data and use this to greatly accelerate research and drug development. Existing areas such as diagnostics and new areas such as precision medicine are both rapidly developing due to the proliferation and increasing usability of clinical and genomic data. Activities such as clinical trial recruitment, collecting real world data (“real world evidence” in FDA phrasing), and understanding exogenous health factors are also being re-conceived because of the huge amount of data being generated by the healthcare system. And at the end of the day, easing friction on these activities via modern software will lead to much better health outcomes for patients and data collection and management is at the heart of this process.

One of Ovation’s most important observations was that medical testing labs (and molecular labs in specific) are underserved by modern software. These labs are responsible for conducting the vast amount of tests that care providers order while treating patients. Large names such as Quest and LabCorp may be familiar but there are many independent testing labs taking on the bulk of this workload. Furthermore, independent labs also conduct the majority of molecular and genetic testing for patient diagnosis. Yet many of these labs are still run on legacy software systems that are cumbersome and inefficient and exist as a major point of friction in lab operations.

Ovation has built a modern SaaS solution targeted directly at the needs of these labs. Their product is a modern cloud-based clinical informatics system that handles all major functions: from patient registry, to managing sample workflows, to storing and organizing the data, and finally to managing the revenue and billing process. By implementing true vertical software, labs are much more efficient in their operations and can quickly measure and analyze their workflows and internal data to provide better services and care to patients. And most importantly, Ovation software offers labs the ability to utilize their clinical and genomic data to improve patient diagnostics and long term outcomes. Ovation is also continuing to build intelligence into their software – learning from workflows in order to continuously help automate the testing process for labs. At Madrona we call these types of software “intelligent applications” and Ovation is a prime example in a vertical that needs modern SaaS options.

We met Barry here in Seattle through Mike Self, of StagedotO, a new seed stage venture partnership and were delighted to find some of the themes we had been discussing internally to be at the crux of Ovation’s business. We could not be more excited to be partnering with Barry and Winston for the next step of the Ovation journey and we are thrilled to help them achieve their vision of unlocking genomic data and clinical informatics in the medical world.

POSTED IN: Madrona News

Innovation where Life Sciences and Computer Science Meet

The Pacific Northwest is a major hub of tech innovation.  It is also a hub for life sciences research, biotech and healthcare innovation.  The past several years have brought increasing convergence of these disciplines, most notably the nexus of life science, computer science and data science.  This combination has been a driver of new breakthroughs — i.e. use of machine learning in discovery, diagnostics and therapeutics.

Our region is home to two of the top market cap companies, Amazon and Microsoft, who are both leaders in cloud technologies. These companies are defining and building the scale infrastructure and platforms, including major advancements in Machine Learning (ML) and Artificial Intelligence (AI), for next generation applications. Major research institutions such as the Fred Hutchinson Cancer Research Center, Allen Institute for AI (Ai2), Allen Institute for Brain Science and a growing ecosystem of companies (e.g., Adaptive) are starting to leverage the power of data, algorithms and computing power to develop breakthrough research and products driving critical improvements in healthcare and global health.

The convergence is enabling new opportunities in the broader healthcare and life sciences markets – spanning from traditional healthcare IT to digital health to diagnostics to next generation therapeutics and automated scientific discovery.  We have already invested in several companies in this area – Saykara which is bringing NLP and AI to the world of medical scribes, Accolade which helps employees get the most out of their healthcare plan using software intelligence and people, and Envisagenics, the recipient of the Madrona/Microsoft AI prize which is applying AI and high-performance computing to uncover novel cures in RNA sequencing data.

In working with entrepreneurs and the local industry, we’ve looked at the broad market, divided it into “more healthcare” and “more life sciences”  and identified areas of specific interest where we see substantial opportunity for software and data-science/AI driven innovation and are within our expertise.  Our map of this intersection is below and we will highlight a couple areas of particular interest.

Diagnostics: In the area of diagnostics, ML and AI techniques are already empowering next generation clinical decision support services into the market.  The application of computer vision to radiology and pathology is one example. Companies such as Zebra, Viz.AI, Imagen, and others have had AI/ML based medical diagnostics achieve regulatory approval in areas such as stroke diagnosis, atrial fibrillation detection, fracture diagnosis, and others.  In the area of cancer diagnosis, new companies such as PAIGE and PathAI are making major strides. In the past year, we’ve seen an increase in new AI-powered offerings achieving regulatory approval in a broad range of diagnostics from stroke to wrist fracture to heart & lung related diagnostics and others.

Infrastructure: To support research and development of new drugs fueled by an understanding of genomics data, there are several important infrastructure categories.  One thing we’ve noted over the past year is that our software and infrastructure companies are seeing growth in this vertical.  One of these is Qumulo, which provides next generation file storage for institutions like the Carnegie Institution for Science which works with terabyte-size data sets alongside millions of tiny sequencing files.

Analytics: On the more traditional IT end of things, we see an opportunity for analytics that overlay systems for running labs, processes, healthcare systems and more to provide better insights and help drive operational efficiency and improved care. KenSci is a good example of a company working on analytics for large hospital systems.

Data: And, underlying each of these categories is a significant need for data.  Data is what will power diagnostic services development, drug discovery, clinical trial matching and many more clinical and research applications. There is a need and opportunity for data providers and ecosystems to leverage the data to drive the innovations we all foresee.  Existing players such as Prognos, Patients Like Me, Tempus, and RDMD are all working on this space and we are excited to see the next wave of innovation in data acquisition and management.

As 2019 unfolds we will continue to share our thoughts and if these areas are of interest to you, please engage us.

POSTED IN: Madrona News

Reaching your Audience – Session with The Verge

Last week we hosted Helen Havlak, Editorial Director of The Verge, to talk about the ever-changing world of digital media, social media, and reaching the audiences you want.  

The Verge is all about making technology news mainstream.  Most recently, they addressed some of the negativity and fear around the future of technology with Better Worlds, a series of 10 science fiction short stories with video and audio adaptations focused on a more hopeful future for technology.  

One of Helen’s responsibilities is to oversee The Verge engagement team.  With the philosophy that readers are using many different channels and might not visit your site, The Verge goes to its readers on the platforms where they live. For B to C companies, Helen offered both practical tips and strategic advice.  Here are some quick highlights.


  • Figure out what your audience wants – education, information, entertainment  – and then create the content around that. Doing a job for your audience is more important than your own marketing agenda.
  • Know what you have in terms of assets.  If your product or story doesn’t lend itself to photos – think hard about a channel like Instagram.  
  • Follow the fads, but invest cautiously – Facebook Groups for example were a big push in 2017, but many have been abandoned due to moderation challenges.  Remember Vine? And think about the future of newer platforms – how will they make money? (what’s in it for them to continue to support other people creating content on their site . . ).
  • Be skeptical of how different platforms count followers and engagement. The Verge sees more likes and comments on Instagram than on Twitter, although Twitter might report higher “impressions.” A YouTube video frequently has 5X as many minutes watched as the same “view” on Facebook.
  • Moderation is very important, especially on YouTube.  Turning off comments kills your placement in the algorithm, and not monitoring offensive comments can create a toxic environment and burn out your talent.  YouTube is an important audience, but make sure you have the resources to support it.
  • If you are producing a video or a podcast a week – create a schedule and stick to it.  Subscribers notice.
  • Know that your audience is mostly going to be on their phone and mostly going to be in an app owned by another company – figure out which of those channels work for you.
  • And while she didn’t talk about it – she showed it – measure measure measure  – that is how you see the trends of platforms that are on the rise or waning.

Photo credit to James Bareham // The Verge

POSTED IN: Madrona News

Why and How Intelligent Applications Continue to Drive Our Investing

Intelligent Applications have been and continue to be a focus of our investing.  These apps sit on top of the infrastructure a company chooses, the data they collect and curate, the machine learning they apply to the data and the continuous learning system they build.  In this deep dive we talk about why intelligent applications are a central component to our investing themes and where we see the opportunities for company creation and building.

Intelligent apps are applications that use data and machine learning to create a continuous learning system that delivers rich, adaptive, and personalized experiences for users. These intelligent apps range from “net-new” apps like those powering autonomous vehicles and automated retail stores to existing apps that are enhanced with intelligence, such as lead scoring in a CRM app or content recommendations in a media app.

Intelligent apps will have a massive impact on the way we work, live, and play, and we have already been blown away by the potential in what we are seeing companies build today. Some of the most exciting intelligent apps we have seen do at least one of the following:

Enable completely new behaviors

Some of the most impressive demonstrations of machine learning are those that use AI to create new business processes and markets that completely change the way people do things. One high-profile example is Amazon Go stores using computer vision to completely change the supermarket or convenience store experience by removing the checkout process.

Another great example is Textio. Textio offers an AI-powered ‘augmented writing platform’ which draws on massive amounts of historical data to help companies write better job descriptions that will attract higher quality applicants. Both of these examples use AI to create new processes that result in better experiences and better outcomes for their users.

Drive 10x (or better) process improvements

AI automation and insights can also be used to optimize existing processes and workflows. Automation using AI is at the cornerstone of what every enterprise is going through in terms of digital transformation.  For example, UiPath’s RPA platform allows companies to drastically reduce costs by automating a wide variety of software based tasks using UiPath’s “robots.” While the UiPath platform is early in its journey to becoming an intelligent app, it is already helping its customer drive 10x process improvements.

Suplari also uses AI to improve existing business processes, namely to analyze purchase behaviors to better understand how to drive cost reductions and manage supplier risks. While Suplari’s customers may have individual processes to reduce software costs through deduplication or to identify opportunities for savings in contract renewals, using AI to proactively identify the best opportunities allows their customers to realize large efficiencies in their procurement processes.

Integrate silos (data and workflows) and capture value

Another great opportunity for AI companies is to combine data and processes to allow companies to combine different parts of the value chain and capture more value. For example, Affirm uses machine learning to approve consumer loans and uses these loans to help ecommerce companies improve shopping cart conversion rates.

One of our portfolio companies, Amperity, literally combines different silos of customer data.  Companies that have customer data stored in disparate systems and tools can’t easily leverage this data to get a full picture of their customer base. Intelligently stitching these silos together drives significant business results for Amperity’s clients who can now clearly see the stitched 360-view of their customers and use it to market and sell products in a more intelligent way.

Trends Converge

Now is an exciting time for investors and entrepreneurs to be focusing on intelligent applications because of the momentum and growth of several important technology trends:

  • Massive computational power and low-cost storage are creating the infrastructure to train machine learning models
  • More data is generated and stored than ever before in many different fields like healthcare, autonomous systems, and media
  • Availability of good-enough capabilities at the edge to do a lot of the inferencing work at the edge as opposed to having to round-trip to the cloud
  • Continued improvement and development in tools and frameworks make it easier for companies and developers to begin using machine learning
  • New “user interfaces” using voice, vision, and touch are bridging the gap between the digital and physical world

As these trends make it easier for entrepreneurs to build intelligent applications, we have been developing our own frameworks to understand how all of these pieces fit together to create value for customers. Generally, we think about the intelligent application ecosystem in three main parts:

  • The Data Platform Layer
  • The Machine Learning Platform Layer
  • The Intelligent Applications and “Finished Services” Layer

The Machine Learning Platform Layer

As an early believer in the potential of AI and machine learning, Madrona has made several investments in the machine learning platform layer, including companies like Turi, Lattice, and Algorithmia. This layer of the intelligent app stack is meant to make it easier for other developers and applications to make use of machine learning by providing the tools and automating tasks such as model training, model deployment, and model management.

The ML platform includes machine learning frameworks like TensorFlow and PyTorch, managed services and tools like Amazon Sagemaker and TVM, as well as “Model as a Service” providers in the form something like AWS Marketplace that can help developers and companies develop and deploy ML models in specific environments. While many of these tools have been developed by large companies or acquired by large companies, we believe there continues to be interesting opportunities at this layer because deploying and managing machine learning systems continues to be very difficult.

As an example, while the major cloud providers have made large investments in software and hardware to train ML models in the cloud, using those models for inference at the edge continues to be a difficult problem on resource-constrained devices. is a portfolio company in this segment that uses software optimizations to improve the quality of machine learning predictions on edge devices that have limited power or bandwidth.

Overall, we believe that while frameworks and tools have been improving, advanced techniques like reinforcement learning still need frameworks and tools that are easier to use, and there are many interesting opportunities to continue improving the ML platforms that intelligent apps depend on.

The Data Platform Layer

A precursor to using AI effectively and building intelligent applications is having a “data” strategy.  Having a unique data strategy that could be a combination of public data sets and proprietary data sets enables companies to provide unique and differentiated value.  This is a necessary first step, before you can use the data to train models and build a continuous learning system that is a core part of building an intelligent application.

Within the Data Platform layer, we think of companies and products from portfolio companies, Datacoral and Snowflake, as well as those from Databricks and Amazon’s Redshift, which offer customers different ways to connect, transform, warehouse, and analyze data in order to be used in an ML platform. What we’ve seen at this layer of the stack is that getting data into the right place, in the right format, in order to be used for machine learning continues to be very difficult, and simplifying this process is extremely valuable to customers.

Additionally, access and ownership to data itself is a key part of the data platform layer. By this, we mean that companies need to be thoughtful about their data strategies in order to find ways to gain access to, generate, or combine different data sources in order to create unique data assets. As we are seeing frequently in the news these days, companies also need to be thoughtful about data privacy and making sure customers understand what data is being used, shared, and how.

The lines between the Data Platform Layer, the ML Platform Layer, and Intelligent Apps themselves can be quite blurry, especially as companies try to offer their customers a broader set of services or learn their way into new customer needs. However, we do see a distinction between companies that are focused on helping customers manage their data vs. helping customers manage their ML models.


Ultimately, we are looking for companies that can benefit from the virtuous data cycle – where more data creates better user experiences, leading to better user engagement, leading to more data, and ultimately better user experiences again.

Intelligent Applications and “Finished Services” Layer

Within the Intelligent Applications and Finished Services layer, there are several ways to segment the market. We like to think about verticals – applications that focus on a specific industry such as healthcare or insurance – and horizontals – cross-industry applications such as marketing automation or robotic process automation. One of the principles that we follow when looking for these types of opportunities is to find areas where data is becoming digitized and/or more data is being collected than ever before.

For example, one promising vertical for intelligent apps is healthcare. Technology and regulatory trends have driven the healthcare field to rapidly digitize many different types of records – from basic medical histories, to insurance claims, to x-rays, MRI scans, and ‘omics’ data (e.g., genomics, proteomics, biomics). This digitization of healthcare is creating new levels of visibility into patient and population health data, and ML will be a critical tool to help decision makers make sense of these new data sources.

Workforce productivity is another promising area for horizontal intelligent applications because more data is digitized than ever before in HR and employee engagement across industries. One example of a horizontal intelligent app is Madrona Venture Labs spinout company, UpLevel, which uses unstructured data from tools like Slack to help managers get better insights on how to best engage their teams and drive productivity.

In addition to vertical and horizontal apps for business users, we also include other types of “finished services” in this bucket. This can include services like Amazon Rekognition or Amazon Forecast, which help application developers add image and video analysis or time series forecasting models to other applications. In this case, the end customer for a product may not be a consumer, but the product is a “finished service” which can be plugged into a customer-facing application.

In each of these use cases, we are looking to find companies that deeply understand customer pain points and use machine learning as a tool to solve customer problems, rather than starting with a technology and searching for use cases.

Areas of Opportunity

We believe that every successful application built today will be an intelligent application, and that is why we think there is a huge amount of opportunity for entrepreneurs in this space. In particular, we would love to see more companies that are building at the nexus of multiple large markets, companies with unique data strategies, and companies with great ML teams (because AI continues to be very difficult). Four specific areas where we are excited to meet new companies are:

  • AI for Healthcare – More healthcare data is digitized and stored than ever before, and this is creating massive opportunities to reduce costs while improving quality of care and operations. The intersection of the biological sciences with computer science is going to be a difficult area to break through, but the potential value created will be huge, and we are looking for entrepreneurs who are ready to take on these challenges.
  • AI for Work – More and more, companies want to measure and become data-driven about productivity, hiring, and employee wellness. Traditionally, HR and workforce data has been incredibly hard to collect and analyze, but new applications like Slack and Workday are creating opportunities for startups like Polly and UpLevel to analyze workplace data to generate insights for employees and managers.
  • Automation – Robotic Process Automation (RPA) vendors are one set of companies building early intelligent apps that can analyze a business process and improve productivity through automation, but they will not be the last. We think there will also be opportunities to build vertical “RPA-like” businesses in specific industries, automation of manual work that can be dangerous and expensive, and new types of autonomous systems like autonomous vehicles.
  • “End-to-End AI” – Many companies have a section of their pitch explaining how valuable their data will be. We always encourage companies to think about the best use cases for their data, and, if it makes sense, execute on those use cases themselves. Some of our favorite examples in this category are companies like Climate Corp, which started with an ML system for predicting weather, found that they could use their predictions to sell weather insurance to farms, and eventually built an end-to-end farm management software system to capture more data and use it to write insurance policies.


During a recent CIO roundtable, we debated whether machine learning was an over-hyped or under-hyped technology trend. The answer in most people’s minds was both. There are incredibly high expectations for machine learning, and many of those expectations are not grounded in the reality of what ML can do today.

However, we believe that as we move forward, the ability to build new applications and continuously improve systems and processes using machine learning will be a core part of any app, and machine learning will be immensely impactful in every fabric of the society that we work and live in.

Current or previous Madrona Venture Group portfolio companies mentioned in this blog post:  Algorithmia, Amperity, Datacoral, Lattice, Snowflake, Suplari, Turi,, UIpath

POSTED IN: Madrona News

Investment Themes for 2019

2018 was a busy year for Madrona and our portfolio companies. We raised our latest $300 million Fund VII, and we made 45 investments totaling ~$130 million.  We also had several successful up-rounds and company exits with a combined increase of over $800 million in fund value and over $600 million in investor realized returns.  We don’t see 2019 letting up, despite the somewhat volatile public markets.  Over the past year we have continued to develop our investment themes as the technology and business markets developed and we lay out our key themes here.

For the past several years, Madrona has primarily been investing against a 3-layer innovation stack that includes cloud-native infrastructure at the bottom, intelligent applications (powered by data and data science) in the middle, and multi-sense user interfaces between humans and content/computing at the top. As 2019 kicks off, we thought it would be helpful to outline our updated, 4-layer model and highlight some key questions we are asking within these categories to facilitate ongoing conversations with entrepreneurs and others in the innovation economy.

For reference, we published our investment themes in previous years and our thinking since then has both expanded and become more focused as the market has matured and innovation has continued.  A quick scan of this prior post illustrates our on-going focus on cloud infrastructure, intelligent applications, ML, edge computing, and security, as well as how our thinking has evolved.

Opportunities abound within AND across these four layers.  Infinitely scalable and flexible cloud infrastructure is essential to train data models and build intelligent applications.  Intelligent applications including natural language processing models or image recognition models power the multi-sense user interfaces like voice activation and image search that we increasingly experience on smartphones and home devices (Amazon Echo Show, Google Home).  Further, when those services are leveraged to help solve a physical world problem, we end up with compelling end-user services like Booster Fuels in the USA or Luckin Coffee in China.

The new layer that we are spending considerable time on is the intersection between digital and physical experiences (DiPhy for short), particularly as it relates to consumer experiences and health care.  For consumers, DiPhy experiences address a consumer need and resolve an end-user problem better than a solely digital or solely physical experience could.  Madrona companies like Indochino, and provide solutions in these areas.  In a different way, DiPhy is strongly represented in Seattle at the intersection of machine learning and health care with the incredible research and innovations coming out of the University of Washington Institute for Protein Design, the Allen Institute and the Fred Hutch Cancer Research Center. We are exploring the ways that Madrona can bring our “full stack” expertise to these health care related areas as well.

While continuing to push our curiosity and learning around these themes, they are guides not guardrails.  We are finding some of the most compelling ideas and company founders where these layers intersect. Current company examples include voice and ML applied to the problem of physician documentation into electronic medical records (Saykara), integrating customer data  across disparate infrastructure to build intelligent customer profiles and applications (Amperity), or cutting edge AI able to run efficiently in resource constrained edge devices (

Madrona remains deeply committed to backing the best entrepreneurs, in the Pacific NW, who are tackling the biggest markets in the world with differentiated technology and business models.  Frequently, we find these opportunities adjacent to our specific themes where customer-obsessed founders have a fresh way to solve a pressing problem.  This is why we are always excited to meet great founding teams looking to build bold companies.

Here are more thoughts and questions on our 4 core focus areas and where we feel the greatest opportunities currently lie. In subsequent posts, we will drill down in more detail into each thematic area.

Cloud Native Infrastructure

For the past several years, the primary theme we have been investing against in infrastructure is the developer and the enterprise move to the cloud, and specifically the adoption of cloud native technologies.  We think about “cloud native” as being composed of several interrelated technologies and business practices:  containerization, automation and orchestration, microservices, serverless or event-driven computing, and devops.  We feel we are still in the early-middle innings of enterprise adoption of cloud computing broadly, but we are in the very early innings of the adoption of cloud native.

2018 was arguably the “year of Kubernetes” based on enterprise adoption, overall buzz and even the acquisition of Heptio by VMware.  We continue to feel cloud native services, such as those represented by the CNCF Trail Map, will produce new companies supporting the enterprise shift to cloud native.  Other areas of interest (that we will detail in a subsequent post) include technologies/services to support hybrid enterprise environments, infrastructure backend as code, serverless adoption enablers, SRE tools for devops, open source models for the enterprise, autonomous cloud systems, specialized infrastructure for machine learning, and security.  Questions we are asking here include how the relationship between the open source community and the large cloud service providers will evolve going forward and how a broad-based embrace of “hybrid computing” will impact enterprise customer product/service needs, sales channels and post-sales services.

For a deeper dive click here.

Intelligent Applications with ML & AI 

The utilization of data and machine learning in production has probably been the single biggest theme we have invested against over the past five years.  We have moved from “big data” to machine learning platform technologies such as Turi, Algorithmia and Lattice Data to intelligent applications such as Amperity, Suplari and AnswerIQ.  In the years ahead, “every application is intelligent” will likely be the single biggest investment theme, as machine learning continues to be applied to new and existing data sets, business processes, and vertical markets.  We also expect to find interesting opportunities in services that enable edge devices to operate with intelligence, industry-specific applications where large amounts of data are being created like life sciences, services to make ML more accessible to the average customer, as well as emerging machine learning methodologies such as transfer learning and explainable AI.  Key questions here include (a) how data rights and strategies will evolve as the power of data models becomes more apparent and (b) how to automate intelligent applications to be fully managed, closed loop systems that continually improve their recommendations and inferences.

For a deeper dive click here.

Next Generation User Interfaces

Just as the mouse and touch screen ushered in new applications for computing and mobility, new modes of computer interaction like voice and gestures are catalyzing compelling new applications for consumers and businesses. The advent of Alexa Echo and Show, Google Home, and a more intelligent Siri service have dramatically changed how we interact with technology in our personal lives.  Limited now to short simple actions, voice is becoming a common approach for classic use cases like search, music discovery, food/ride ordering and other activities.  Madrona’s investment in Pulse Labs gives us unique visibility into next generation voice applications in areas like home control, ecommerce and ‘smart kitchen’ services. We are also enthused about new mobile voice/AR business applications for field service technicians, assisted retail shopping (E.g., Ikea’s ARKit furniture app) and many others including medical imaging/training.

Vision and image recognition are also rapidly becoming ways for people and machines to interact with one another as facial recognition security on iPhones or intelligent image recognition systems highlight. Augmented and virtual reality are growing much more slowly than initially expected, but mobile phone-enabled AR will become an increasingly important tool for immersive experiences, particularly visually-focused vocations such as architecture, marketing, and real estate.  “Mobile-first” has become table stakes for new applications, but we expect to see more “do less, but much better” opportunities both in consumer and enterprise with elegantly designed UIs.  Questions central to this theme include (a) what ‘high-value’ new experiences are truly best or only possible when voice, gesture and the overlay of AR/VR/MR are leveraged? (b) what will be the limits of image (especially facial recognition) in certain application areas, (c) how effective can image-driven systems like digital pathology be at augmenting human expertise, and (d) how will multi-sense point solutions in the home, car and store evolve into platforms?

For a deeper dive click here.

DiPhy (digital-physical converged customer experiences)

The first twenty years of the internet age were principally focused on moving experiences from the physical world to the digital world. Amazon enabled us to find, discover and buy just about anything from our laptops or mobile devices in the comfort of our home.  The next twenty years will be principally focused on leveraging the technologies the internet age has produced to improve our experiences in the physical world. Just as the shift from physical to digital has massively impacted our daily lives (mostly for the better), the application of technology to improve the physical will have a similar if not greater impact.

We have seen examples of this trend through consumer applications like Uber and Lyft as well as digital marketplaces that connect dog owners to people who will take care of their dogs (Rover).  Mobile devices (principally smartphones today) are the connection point between these two worlds and as voice and vision capabilities become more powerful so will the apps that reduce friction in our lives.  As we look at other DiPhy sectors and opportunities, one where the landscape will change drastically over the coming decades is physical retail.  Specifically, we are excited about digital native retailers and brands adding compelling physical experiences, increasing digitization of legacy retail space, and improving supply chain and logistics down to where the consumer receives their goods/services.  Important questions here include (a) how traditional retailers and consumer services will evolve to embrace these opportunities and (b) how the deployment of edge AI will reduce friction and accelerate the adoption of new experiences.

For a deeper dive click here.

We look forward to hearing from many of you who are working on companies in these areas and, most importantly, to continuing the conversation with all of you in the community and pushing each other’s thinking around these trends.  To that end, over the coming weeks we will post a series of additional blogs that go into more depth in each of our four thematic areas.

Matt, Tim, Soma, Len, Scott, Hope, Paul, Tom, Sudip, Maria, Dan, Chris and Elisa 

(to get in touch just go to the team page – our contact info is in our profiles)

POSTED IN: Madrona News

Why We Are Doubling Down On Shyft

We are excited to announce today our Series A investment in Shyft.

Since investing in Shyft’s seed round nearly two years ago, we have watched Brett Patrontasch (CEO) and team continue to make impressive progress against their goal of reinventing the way hourly workers manage their shifts and the way national employers both manage and support their workforce.

We originally met Brett through our involvement and support of the TechStars program.  Shyft taps into our love of supporting scrappy entrepreneurs using technology to change people’s lives for the better.  Through a mobile cloud connected application, Shyft enables a workforce that has little control over their schedule to take control by easily swapping shifts.  Shyft started as a ground up platform that appealed to workers at Starbucks and many other retail chains, and, over the past two years, managers have taken note.

Shyft has responded by creating an enterprise software solution that enables retail outlets to manage their workforce while providing the flexibility that employees value.

This all comes at a crucial time in how the expectations of the modern workforce are changing and along with that, the move to create rules that protect this growing workforce.  Cities and legislatures around the country are taking a close look via Secure Scheduling (also known as Predictive Scheduling) at how these hourly workers are scheduled – and creating protections that require some stability of schedule.  This is a great thing, and as companies are required to support these regulations they need solutions like Shyft.

The proof is in the customers – and Gap has adopted the Shyft platform as their workforce management platform for all of their brands – Old Navy, Banana Republic, Althleta.  Companies such as the Gap are adopting Shyft because the app creates real collaboration amongst employees which helps with productivity and general satisfaction.

We are investing alongside Ignition Partners for this round and it is great to work with them again.

The team’s relentless focus on product and end user experience is inspiring and is winning them new customers every day. Brett and his team are extremely passionate about the market and their product and we believe that they’ve created a game changing company poised for continued success.

POSTED IN: Madrona News

Apptio and TBM’s Next Journey

The journey from Day One to building a successful customer base, company and market category is exhilarating! As company building partners, we are honored to work with great entrepreneurial teams every day. One of the most special companies and groups of people we have ever worked with is Apptio. Today is a major moment in Apptio’s 11-year company life and is the beginning of the next phase of their journey.

Apptio’s five founders, led by CEO Sunny Gupta, started the company in the fall of 2007. Their passion was to help Information Technology (IT) and finance organizations at large enterprises better manage the business of IT. As virtualization, and later cloud computing, were increasingly adopted in big companies, the technology business leaders didn’t have adequate management tools. Apptio started by categorizing and connecting the IT data around hardware, software and services costs with the finance and accounting cost systems. Over time this costing service was combined with SAAS-based planning, decisioning and agile learning systems. And, Apptio became the underlying system of record for enterprise CIOs. Within a few years, they were servicing several of the largest customers in the world and pioneered the category of Technology Business Management (TBM).

Sunny Gupta and I first met in 2001. From that first meeting, we both somehow knew that we were going to work together for many years to come.

He was and is one of those rare innovators who combines customer-centricity, product passion and genuine humility in an authentic way. And, he inspires teams to achieve their full potential.

We first worked together at Performant which was my first VC investment. In the spring of 2003 Performant was acquired.  In early 2005, Sunny, Jeff Gerber and I partnered to found and seed iConclude to automate IT “runbooks”. During those next few years, we added a great CFO in Kurt Shintaffer and outstanding co-investors Tom Bogan (then at Greylock) and Ravi Mohan from Shasta Ventures. iConclude was then acquired by Opsware.

While at Opsware, Sunny got increasing exposure to enterprise CIOs and the finance people who were helping understand and allocate the IT costs to different business units and teams. When Opsware was bought by HP in summer 2007, Sunny knew that a bigger opportunity was on the horizon to build a systematic way to align IT business units and finance. So, in the fall of 2007, we “brought the band back together” and started Apptio.

Apptio’s 11-year journey to date has, like every start up, included great mountaintop moments and a few low points. The highlights included early customer wins at companies like Cisco, Goldman Sachs and First American. Equally important were incredible executive hires including Larry Blasko, Chris Pick and Dione Hedgpeth. And, the company helped create and build a movement around cost transparency and data-driven decision making known as Technology Business Management. These successes were balanced with an early over-reliance on platform technology over finished SAAS apps and the occasional executive hire who proved not to be the best fit. But, by almost any measure, Apptio is an amazing success story.

On the financing front, Apptio raised several private rounds of private capital – each at a higher valuation. Then, in September 2016, the company went public at $16 per share and opened the first trading day at almost $24 per share. I will always cherish the celebration in New York City with the Apptio founders, team members customers and board!

Apptio missed Wall Street’s earnings expectations their second quarter as a public company causing some investors to lose faith and the stock to drop to under $12. But, Sunny and the Apptio team showed their resilience by clarifying priorities, building use-case specific applications and improving operational execution. In time, the business regained growth and momentum and the stock rallied back above the IPO price.

Throughout the Apptio journey, strategic and financial partners have had a strong desire to work with and invest in the company. Apptio’s strategic perspective on the enterprise journey to hybrid cloud and breadth of CIO relationships may be unmatched. Today, the company announced that it has entered into an agreement to be acquired by Vista Equity at a $38 share price or total equity value of approximately $1.94 billion.

Vista has a strong track record of investing in quality SAAS software companies like Marketo and Cvent and building even more value in those businesses.  When the acquisition closes, Sunny and the Apptio team will partner with Vista so they can best help enterprise customers fully embrace their cloud computing applications over the long-term. And, I am highly confident they will be aligned with their new investor partners to do just that!

For myself and Madrona, it is a day of mixed emotions. When the acquisition is finalized, we will no longer have a direct role with Apptio. I will greatly miss our spirited strategy discussions, the problem solving on hard challenges and the celebrations of successes. Which really means, I will miss the more frequent interactions with Apptio’s amazing board, executives and broader team. I can’t wait to see all the great things Apptio does under Sunny’s leadership in the years ahead.

Finally, I have no doubt that the Apptio team will be lifelong friends. Whether we are helping to build other companies together, making a positive difference in our community or cheering on our beloved Seahawks, we will be serving the Seattle innovation ecosystem for many years to come. And, in my heart, I will always be an Apptian!

Additional Information and Where to Find It

This communication is being made in respect of the proposed transaction involving Apptio, Inc. (“Apptio”) and Bellevue Parent, LLC (“Bellevue”).  In connection with the proposed transaction, Apptio intends to file and furnish relevant materials with the Securities and Exchange Commission (the “SEC”), including a proxy statement on Schedule 14A. Promptly after filing its definitive proxy statement with the SEC, Apptio will mail the definitive proxy statement and a proxy card to each stockholder of Apptio entitled to vote at the special meeting relating to the proposed transaction. This communication is not a substitute for the proxy statement or any other document that Apptio may file with the SEC or send to its stockholders in connection with the proposed transaction. The proxy statement described above will contain important information about the proposed merger and related matters. BEFORE MAKING ANY VOTING DECISION, STOCKHOLDERS OF Apptio ARE URGED TO READ THESE MATERIALS (INCLUDING ANY AMENDMENTS OR SUPPLEMENTS THERETO) AND ANY OTHER RELEVANT DOCUMENTS IN CONNECTION WITH THE PROPOSED TRANSACTION THAT Apptio WILL FILE WITH THE SEC WHEN THEY BECOME AVAILABLE BECAUSE THEY WILL CONTAIN IMPORTANT INFORMATION ABOUT Apptio AND THE PROPOSED TRANSACTION. The definitive proxy statement and other relevant materials in connection with the proposed transaction (when they become available), and any other documents filed by Apptio with the SEC, may be obtained free of charge at the SEC’s website ( or at Apptio’s website ( or by contacting Apptio’s Investor Relations at ir(Replace this parenthesis with the @ sign)

Participants in the Solicitation

 Apptio and its directors and executive officers may be deemed to be participants in the solicitation of proxies from Apptio’s stockholders with respect to the proposed transaction. Information about Apptio’s directors and executive officers and their ownership of Apptio’s common stock is set forth in Apptio’s proxy statement on Schedule 14A filed with the SEC on April 19, 2018, and Apptio’s Annual Report on Form 10-K for the fiscal year ended December 31, 2017, which was filed with the SEC on February 21, 2018. Additional information regarding the potential participants, and their direct or indirect interests in the proposed transaction, by security holdings or otherwise, will be set forth in the proxy statement and other materials to be filed with SEC in connection with the proposed transaction.

Notice Regarding Forward-Looking Statements

 This communication, and any documents to which Apptio refers you in this communication, contains not only historical information, but also forward-looking statements made pursuant to the safe-harbor provisions of the Private Securities Litigation Reform Act of 1995. These forward-looking statements represent Apptio’s current expectations or beliefs concerning future events, including but not limited to the expected completion and timing of the proposed transaction, expected benefits and costs of the proposed transaction, management plans and other information relating to the proposed transaction, strategies and objectives of Apptio for future operations and other information relating to the proposed transaction. Without limiting the foregoing, the words “believes,” “anticipates,” “plans,” “expects,” “intends,” “forecasts,” “should,” “estimates,” “contemplate,” “future,” “goal,” “potential,” “predict,” “project,” “projection,” “target,” “seek,” “may,” “will,” “could,” “should,” “would,” “assuming,” and similar expressions are intended to identify forward-looking statements. You should read any such forward-looking statements carefully, as they involve a number of risks, uncertainties and assumptions that may cause actual results to differ significantly from those projected or contemplated in any such forward-looking statement. Those risks, uncertainties and assumptions include, (i) the risk that the proposed transaction may not be completed in a timely manner or at all, which may adversely affect Apptio’s business and the price of the common stock of Apptio, (ii) the failure to satisfy any of the conditions to the consummation of the proposed transaction, including the adoption of the merger agreement by the stockholders of Apptio and the receipt of certain regulatory approvals, (iii) the occurrence of any event, change or other circumstance or condition that could give rise to the termination of the merger agreement, (iv) the effect of the announcement or pendency of the proposed transaction on Apptio’s business relationships, operating results and business generally, (v) risks that the proposed transaction disrupts current plans and operations and the potential difficulties in employee retention as a result of the proposed transaction, (vi) risks related to diverting management’s attention from Apptio’s ongoing business operations, (vii) the outcome of any legal proceedings that may be instituted against us related to the merger agreement or the proposed transaction, (viii) unexpected costs, charges or expenses resulting from the proposed transaction, and (ix) other risks described in Apptio’s filings with the SEC, such as its Quarterly Reports on Form 10-Q and Annual Reports on Form 10-K.  Forward-looking statements speak only as of the date of this communication or the date of any document incorporated by reference in this document. Except as required by applicable law or regulation, Apptio does not assume any obligation to update any such forward-looking statements whether as the result of new developments or otherwise.

POSTED IN: Madrona News

Allen School Industry Affiliates Day and the 2018 Madrona Prize

Tim Porter, Madrona, and Hank Levy, Allen School,  bracket the winners of the Madrona Prize and Runners Up

Again this year, it was a fun and inspiring night at UW Allen School of Computer Science & Engineering.  Every year we look forward to the day of presentations and then the frantic round robin of poster sessions in the evening.  It is inspiring and humbling to attend and listen to the invention and creative thinking that goes on at the Allen School.  And this year there were many breakthrough projects that spanned disciplines and schools at the University of Washington.  We also see this collaboration and collision of disciplines, particularly data science, computer science and life science,  in companies being built in the greater Seattle region and it is something we are excited about investing in as we move into our next 20 years.

Every year we award the Madrona prize to the most commercially viable ideas presented.  This year the winners were as follows.

Madrona Prize Winner

EMBARKER: A hierarchical Bayesian approach empowering big data with prior knowledge for expression marker discovery and its application to Alzheimer’s disease

Safiye Celik, Josh C. Russell, Cezar R. Pestana, Ting-I Lee, Shubhabrata Mukherjee, Paul K. Crane, C. Dirk Keene, Jennifer F. Bobb, Matt Kaeberlein

Advisor: Su-In Lee


Runners Up

Puddle: A System for High-Level Microfluidic Programming
Max Willsey, Ashley Stephenson, Chris Takahashi, Pranav Vaid, Bichlien Nguyen, Michal Piszczek, Christine Betts, Sharon Newman, Sarang Joshi

Advisors: Karin Strauss and Luis Ceze

Slim: OS Kernel Support for a Low-Overhead Container Overlay Network
Danyang Zhuo, Kaiyuan Zhang, Yibo Zhu, Hongqiang Harry Liu, Matthew Rockett,

Advisors: Arvind Krishnamurthy and Tom Anderson

Implantable Wireless Brain-Computer Interface
Jared Nakahara, Vaishnavi Ranganathan, Soshi Samejima, Nicholas Tolley, and Chet Moritz. See this for background on this poster.

Advisor: Joshua Smith

Press Release

POSTED IN: Madrona News