Solving the big problem facing autonomous vehicles

Training and testing on way more edge cases, for dramatically improved smoothness and safety.



Building automated transportation systems means solving for the millions or more of risky traffic scenarios which individually are unlikely, but together make up the bulk of the risk.

But for the AV developer it's challenging to know how many edge cases there are, much less have certainty your AV will be able to handle all of them.

How can cities, municipal transit authorities, government regulators and developers know that AVs are safe before they hit the streets?


dRISK is integrating a massively diverse set of data and expert curation into the ultimate data resource for AVs. Rather than enumerating each one of an infinite set of edge cases, we invented a way to “map” all edge cases into a comprehensive taxonomy - a knowledge graph of risk - which acts as both an edge case database and evaluation space.

dRISK’s patented technology trains, tests and validates AVs on comprehensive sequences of edge cases derived from our massive knowledge graph. The result is a step increase in AV responsiveness and safety.

Along with our partners, we have been given a mandate to develop this technology into the first true driver's test for AVs.

Customers and Partners

dRISK currently serves some of the world's leading AV developers, transport authorities and insurers to train, test and validate autonomous vehicles before they are deployed.

We also work closely with a consortium of collaborators consisting of Imperial College London, Claytex Services Limited, DG Cities and Transport for London. Our group has collectively won a £3.6M grant from the UK's Department for Transportation and Innovate UK to commercialize our driver’s test for AVs.

For more information, email us at


2019-09-26: dRISK raises $675k Seed Funding in round led by Okapi VC, with additional investment from Netsu Equity, SaaS Ventures and Poetic Partners.

2018-07-30: Traffic Technology Today - "A current UK government project, seen as an essential stepping stone towards end-to-end validation of autonomous systems through simulation."

2018-07-30: dRISK Consortium wins £3M in grantfunding to commercialize a groundbreaking vehicle safety framework and AV training, test and validation platform.


Chess Stetson, Ph.D.

Chess Stetson, Ph.D.

CEO. Chess completed his doctoral and post-doctoral work in Computation and Neural Systems at Caltech, and previously earned an AB in Physics from Harvard. He has more than a dozen peer-reviewed publications in experimental and computational neuroscience, 3 patents issued and 3 pending, and has spent years building and refining dRISK's core knowledge graph IP and providing AI/ML solutions to Fortune 500 companies, large integrated healthcare providers, financial services firms and autonomous vehicle companies. He also occasionally appears as a neuroscience expert on National Geographic’s Brain Games.
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Nils Goldbeck, Ph.D.

Engineering Lead. Nils earned his Ph.D. in Transportation and Operations Research at Imperial College London. His research focused on a novel method for analysing the resilience of interdependent infrastructure systems with network flow models. Previously Dr. Goldbeck earned an MPhil in Engineering for Sustainable Development at the University of Cambridge.

Brett Kennedy

Robotics Advisor. Brett is currently a Principal Engineer at the Jet Propulsion Laboratory and the Supervisor of the Robot Vehicles and Manipulators Group. Brett began his career in 1997 after receiving a B.S. in Mechanical Engineering from UC Berkeley and a Masters from Stanford. Brett has led a number of development programs in high reliability robotic systems for sponsors such as NASA, DARPA, DTRA, and the US Army; notable roles have been the Lead Engineer for the Robotic Arm aboard the Mars Science Laboratory (MSL) rover (Curiosity), and the Principal Investigator for JPL's entry to the DARPA Robotics Challenge.
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Kiran Jesudasan

Transportation Systems Specialist. Kiran earned his Masters's degree in transportation systems design from ArtCenter College of Design and has experience in working for VW India, automotive consulting and autonomous vehicle service design. His area of focus is identifying needs and defining opportunity space at the intersection of AV deployment strategy, transportation policy, and safety validation.
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Sam O'Connor Russell

AI Engineer. Sam completed his MSc in Artificial Intelligence at the University of Edinburgh in 2019, with a focus in machine learning and Bayesian statistics. Sam has experience applying neural networks to solve problems in areas such as natural language processing and computer vision. His dissertation focused on the application of statistics and machine learning to model the development of stem cells.
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Rav Babbra

Business Development and Programme Manager. Rav is a chartered engineer with chartered project manager skills and 15 years of experience within multi-disciplined engineering environments and a record of successfully delivering complex global engineering projects. Rav advises dRISK on high-level partnerships and programme management. He holds a Bachelor's of Science from University of Plymouth in Electrical Engineering.
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Mariya Pozdeyeva

Simulation engineer. Mariya is working on dRISK's in-house simulation capabilities, focusing on vehicle physics and road user animations. She holds an MEng in Civil & Environmental Engineering from Imperial College London and has completed her final year project on trajectory optimisation for AVs at unsignalised intersections. She is currently also studying towards an MSc in Transport Engineering at Imperial College.
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...this could be you

dRISK is hiring talented, creative and diverse individuals to help us polish off the solution to the world's greatest AI problem. Interested?


dRISK has offices in the London Connectory, London's hub for transportation technology businesses, and in Idealab, one of California's most venerable startup incubators located near Caltech and the Jet Propulsion Laboratory.

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