SaviBrain Inc
Applied AI for human performance and understanding.
We build software that helps people think clearly under pressure, and understand their own patterns well enough to change them. Our models run on your device, so the data that makes them useful never has to leave it.
What we build
Narrow tools that do one difficult thing well.
General-purpose assistants give general-purpose advice. We are interested in the opposite: small, focused applications with enough domain grounding to say something specific.
01
Performance under pressure
The hardest problems in skilled performance are rarely about skill. They are about executing what you already know when it counts. We build preparation routines, in-the-moment regulation, and honest debriefs afterward.
02
Understanding your own patterns
A record of what happened is not the same as insight. We build the layer that reads your history back to you and turns it into an observation specific enough to act on next time.
03
Domain-grounded models
We fine-tune compact models against real expertise (performance psychology, coaching practice) and evaluate them against that standard rather than against generic benchmarks.
How we work
On-device first, and not as a marketing position.
The information that makes a performance tool useful is the information people are least willing to hand over. We treat that as an engineering constraint rather than a policy problem.
Your data stays on your device
Clutch has no backend. Your profile, match history, and coaching results persist locally on your device. There is nothing on a server of ours to breach, subpoena, or sell.
No account, no tracking
We do not ask you to sign up, and we do not include third-party advertising, analytics, or tracking SDKs in our apps.
It has to work offline
Once the on-device model is downloaded, coaching works with no network at all. That matters on a court, and it matters more for knowing where your data went.
A fallback that always works
Every AI feature has a deterministic path behind it. If a device can't run the model, the app stays fully usable rather than degrading into an error message.