Robocurve

Robocurve

Evaluating robots in the real world.

San Francisco
2 employees
Hard Tech
Seed

About Robocurve

Robocurve builds open-source tools and independent benchmarks to measure how well robots can do real-world jobs. Instead of relying on unverified demo videos from frontier labs, we score their models on reproducible benchmarks that anyone can trust.

Today there are no well-run, standardized robotics benchmarks. Labs evaluate in-house, and no independent group has stepped in to run continuous benchmarking as a service. The result is that no one actually knows how good anyone else is, or where the real frontier sits.

Good benchmarks require operating and maintaining physical hardware and real-world setups. Simulation only goes so far, since models that look strong in sim can show large performance gaps once deployed in the real world. Building real-world benchmarks means coordinating job-domain experts, evals engineering, and hands-on robotics all at once.

Frontier labs are targeting general-purpose robotics by 2028, yet the field of robotics evals barely exists. Whoever builds the trusted measure of robot capability becomes the reference everyone relies on. We combine backgrounds in AI evals and robotics to build and grow this field as fast as possible. We already shipped v1 of our open-source framework, Inspect Robots, and ran our first pilot scoring a frontier model on a real robot.

Company details

Team Size2
LocationSan Francisco
IndustryHard Tech

Funding

Last stage

Seed

Investors

Y Combinator

Founders

AZ

Aris Zhu

Founder and CTO of Robocurve. Studied CS & Physics at Harvard. Aris builds robotics systems and AI agents across research and production. At Amazon AGI Labs, her test-time scaling research improved the NovaAct browser agent on WebVoyager. At Yondu Robotics (YC W24), she architected the navigation stack and fleet management system for humanoid robots. At Amazon Robotics she deployed a vision model to edge devices in production. She co-authored a paper in IEEE Robotics and Automation Letters.

LinkedIn
Jay Chooi

Jay Chooi

MA Statistics and BA CS/Math from Harvard. Previously Research Fellow at MATS, researcher at the UK AI Security Institute, and top contributor to Inspect Evals, the UK government's AI eval framework. Rhodes Scholar and gold medalist at the International Olympiad on Astronomy and Astrophysics.

LinkedIn

What happens next.

No applications, no recruiter spam. Just the intro.

01

Confirm the fit

A few questions to make sure this role is the right shape for you. Two minutes.

02

I pitch you to the company

I write the intro, send it to the founder, and handle the back-and-forth.

03

A meeting lands on your calendar

If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.