Google Cloud vets launch Seattle startup Kaskada to bolster machine learning tech with real-time data

Google Cloud vets launch Seattle startup Kaskada to bolster machine learning tech with real-time data

2:28pm, 2nd August, 2019
The Kaskada leadership team, from left to right: Davor Bonaci, Ben Chambers, and Emily Kruger. (Kaskada Photo) After spending several years working at Google Cloud, and saw an opportunity to help companies take better advantage of machine learning technology. Their idea turned into , a Seattle-based startup that is launching out of stealth mode and unveiling its software that uses real-time, event-based data to bolster machine learning features. Davor Bonaci. (Kaskada Photo) More and more companies are implementing machine learning capabilities into their workflows to serve up better recommendations, detect fraud, and other related applications that use the burgeoning technology. But Kaskada contends that these models aren’t using the most up-to-date information, resulting in stale data and poor predictions that don’t accurately reflect the needs of a given user. The startup’s tools let companies implement machine learning features that fully take advantage of up-to-date streaming data. “There is lots of evidence that this is not done as well as it could be done,” Bonaci said of using real-time data. “Companies are leaving money on the table.” Kaskada has raised $1.8 million from investors including Voyager Capital; NextGen Venture Partners; Founders’ Co-op; and Bessemer Venture Partners. The company, founded in January 2018, employs four people and expects to grow. In March it hired , a veteran of Amazon Web Services, as vice president of product. We caught up with Bonaci for this , a regular GeekWire feature. Continue reading for his answers to our questionnaire. What does your company do? Kaskada is a machine learning studio that uses event-based data to compute feature vectors for machine learning in real time. Kaskada empowers data scientists by allowing them to discover, test, and deploy features from event-based data sources in a collaborative, version-controlled environment. By empowering data scientists we help organizations make better predictions and drive more impact from machine learning. Inspiration hit us when: All the time — we’re inspired by progress. Every conversation with data scientists and data leaders helps us refine our vision and make a better, more impactful product. VC, Angel, or Bootstrap: VC. We’ve been incredibly lucky with our investors so far, which include Voyager Capital, NextGen Venture Partners, Founders’ Co-op, and Bessemer Venture Partners. We are also supported by a group of angels that includes directors and senior vice presidents of companies like Google, Twitter and Yelp. Not only have they provided the working capital, but they are also meaningfully helping build the company. Their insight, personal networks, and day-to-day support have been instrumental in getting where we are today. The value we have gotten from our investors is as important — if not more important — than the funding itself. Our ‘secret sauce’ is: Streaming data of course! Our team has deep experience in building distributed systems for data streams and data processing and believe we can fundamentally change how ML is practiced by helping companies harness the power of real-time data. The smartest move we’ve made so far: We came to the startup world with a lot of experience in the data space which also meant we had many existing opinions and biases about it. It can be hard to listen carefully, probe, and ask the right questions if you think you already know the answer. It was important for us to forget what we thought we knew and look at the space with fresh eyes. We also had to be willing to admit when we were wrong and refocus our direction based on what we heard from customers. Putting the customer stories first allowed us to learn and ultimately make much better decisions about product and company direction than we would have made in a vacuum. The biggest mistake we’ve made so far: Gauging time it will take to get to major milestones. Everything takes longer than you expect that it will — particularly if you’re an optimistic person! Sometimes those same delays can end up ultimately being positive, though, as you realize a much better way of achieving the same goal. Which leading entrepreneur would you most want working in your corner? Success doesn’t depend on a single individual. We believe that building a strong team that can work together toward a common vision is more important than any single individual. Our favorite team building activity is: Game night! We have a weekly team game night and (optional) whiskey tasting. We typically play various cooperative board games, which makes it more about winning together. Our current favorite is Hanabi. The biggest thing we look for when hiring is: Culture fit. Building a company is a journey requiring significant growth — both personally and as a group. We’re looking for people who want to be part of that journey and actively participate in that growth. We’re looking for people who would have fun participating in lively discussions as we seek to push each other and the company to be the best we can be. What’s the one piece of advice you’d give to other entrepreneurs just starting out: Pick your team and supporters wisely. They will make you or break you. No other early decision is more important than that one. When you start a new company, there are many people seeking to be involved. Regardless of the role, you’ll hear how much they can help you. But, there are no shortcuts; you and your team will have to solve the hard problems. Always focus on the team and the people who are committed to the long-term success of the company.
Food safety monitoring tech startup wins first place at Madrona machine learning hackathon

Food safety monitoring tech startup wins first place at Madrona machine learning hackathon

12:45pm, 8th May, 2018
The HyperAI team, from left to right: Benji Barash, Yves Albers, Dave Matthew, and Elizabeth Nelson, with TiE Seattle board member Shirish Nadkarni and Madrona Venture Labs CTO Jay Bartot. (Not pictured, from the Hyper AI team: Ritesh Desai and Joaquin Zapeda) (Photo via Madrona) Food safety is a pressing issue. The latest example came last month when an elusive strain of E. coli linked to romaine lettuce sickened 121 people across 25 states and killed one, for how food is screened for safety and quality. Now a newly-formed group of entrepreneurs wants to use machine learning technology to help keep food free of harmful bacteria and containments before it reaches the dinner table. Hyper AI took home the first place prize at a hosted by TiE Seattle and Madrona Venture Labs, the startup studio housed inside Seattle-based venture capital firm Madrona Venture Group. The event featured eight teams who came together last month and spent this past weekend creating startup ideas that incorporated the latest machine learning and deep learning technology. Eight teams participated in the Machine Learning Startup Creation Weekend at Madrona Venture Labs. (Photo via Madrona) The winning team, Hyper AI, aims to help the food industry with hyper-spectral imaging tech that can detect everything from foreign objects to deadly bacteria. It plans to deploy edge devices on customer premises and do the heavy lifting for image analysis with machine learning in the cloud. The group, made up of Amazon vets and experienced technologists, explained that existing solutions are either too manual and expensive, or too specialized. It hopes to use machine learning to improve the food scanning technology over time as it learns how to detect more and more contaminants. “They were able to demonstrate why there is increasing awareness of the issue and demand for new, innovative solutions,” said Mike Fridgen, CEO of Madrona Venture Labs who helped judge the pitches. “They had defined their beachhead opportunity, where they would start, through in-depth conversations with potential food processor customers.” As the first place prize winner, the Hyper AI team will now meet with Madrona Venture Labs with a chance to land a $100,000 investment and participate in , which just . Accepted startups in the accelerator will use Madrona Venture Labs resources — expertise in company creation, design, engineering, etc.; access to Madrona’s advisor and investor network; and more. It will be housed in Madrona’s that opens later this summer underneath its existing downtown Seattle office. Madrona Venture Labs held in the past and ended up investing in the winning companies. The studio is focusing on supporting “vertical” machine learning and artificial intelligence startups, as explained . The second place team from last weekend’s event was FireWise, which aims predict wildfires before they happen. The third place team, HealthShop, wants to help guide healthcare patients to surgery centers. (Editor’s note: I was one of the six judges at the event. Others included Madrona Venture Labs CEO Mike Fridgen; Flying Fish Managing Partner Heather Redman; Madrona Ventures Venture Partner and University of Washington professor Dan Weld; Koru CEO Kristen Hamilton; and Microsoft GM Sona Vaish Venkat )