2labsAbout
AI shouldn't be another feature inside software. It should change how software works.
2labs is an AI-native product studio founded in 2026. We build software where agents do the work and people make the decisions — starting with the document-heavy operations that run the world's businesses.
Our story
Why we started 2labs.
Every company we talked to had the same story: a team of smart people spending most of their day moving information between systems — reading documents, copying fields, chasing approvals. The software they used made each step slightly faster, but never removed the steps.
Then frontier models crossed a threshold. Suddenly a machine could read a hundred-page file, understand it, and act on it — not perfectly, but well enough to change the economics of entire workflows. We started 2labs to build the products that take advantage of that shift.
We're not interested in chatbots or copilots that draft text for humans to fix. We're interested in systems where the agent does the work end to end, and the human's job becomes review, judgment and exception handling. That's what AI-native means to us.
What we believe
- 01The unit of software is shifting from the feature to the outcome.
- 02Agents will do most knowledge work within a decade — the question is whether they'll do it well.
- 03Trust is earned through audit trails and escalations, not marketing.
- 04The best AI products feel boring: work just gets done.
Founders
David Fox
Founder & CEO
David previously worked at Glum before starting 2labs. He leads product and works directly with the design partners who shape Relay.
Kevin Johnathan
Co-founder & CTO
Kevin previously worked as a senior developer in Texas. He leads engineering — agent orchestration, evaluation and reliability.
We're a small, senior team by design. Everyone at 2labs ships product, talks to users and reviews agent output — there are no layers between the people building and the people using.
How we work
Our operating values.
Craft over hype
We'd rather ship one workflow that genuinely works than ten demos that almost do. The bar is: would we trust this with our own operations?
Small team, high leverage
We stay deliberately small and let AI multiply what each person can do — in our products and in how we build them.
Honest about limits
AI agents are powerful and imperfect. We say clearly what our products can and can't do, and we design for the failure cases first.
Close to the work
We sit with the people doing the workflow before we write a line of code. The best product insights are in the messy details nobody writes down.
Want to build the next generation of software with us?
We work with a small number of design partners and we're always happy to meet people who care about this problem.
Get in touch →