Harlen
An AI assistant for personal trainers. Every client gets their own context model holding their wearable data and injury history, plus the notes logged after each session. Overnight, Harlen reads each model against that client's own baseline, ranks who has drifted and drafts their programming and check-ins, which wait until the trainer sends them.
I built the eval harness that decides which changes reach production. It replays coach questions with known answers against a frozen roster of fake athletes, where deterministic checks confirm every number in a reply traces back to the data and stays on the right client. Coaching quality is graded by pass/fail LLM judges, each aligned against about 100 human labels before it counts, so a model swap only goes out once it matches the old score.
- $6K non-dilutive funding
- 5 businesses in beta
- 50+ customer interviews
- pre-launch
context engineering · llm evals · wearables · ios