/ who we work with
Built for teams that need to know.
We work with people whose product or research depends on a language model doing the right thing, and who want evidence rather than a demo.
/ customers
Who we help.
- product teams
Teams shipping agents
Your agent demos well, but you are not sure how it behaves on the long tail of real requests, or whether last week's change made it better.- Evaluation suites from your real traffic and workflows
- Regression checks before each release
- Failure analysis you can act on
- startups
Founders building on LLMs
You need to know whether fine-tuning is worth it, which model to bet on, and how to prove quality to customers without a research team.- A quick, honest read on feasibility
- Evaluation you can show to customers
- Post-training when it is justified
- research
Research groups and labs
You have a question about rewards, verifiers or evaluation and want a partner who cares about method and limitations as much as results.- Joint problem statements
- Reproducible setups
- Write-ups that state their conditions
- enterprise
Companies adapting open models
You want an open-weight model to handle your domain on your infrastructure, with evidence that it improved and stays inside clear boundaries.- Post-training with RLHF, RLVR or preference methods
- Held-out evaluation on your tasks
- Controlled execution and clear resource limits
/ sound familiar
Problems we hear.
“It works in the demo.”
Real requests are messier than the examples you tested. We build the tasks that show you where it breaks.“The score went up.”
A higher reward or benchmark is a reason to look closer. We check whether behaviour improved on tasks the training never saw.“Should we fine-tune?”
Sometimes better prompts, tools or evaluation are enough. We tell you which, before you spend on training.