An applied AI studio, shipping small useful things.
KiteLabs builds focused apps powered by frontier models, retrieval and agentic workflows. The bet is simple — the AI capability is here; the missing piece is product judgement.
The capability is here. The product judgement isn't — yet.
Frontier models can now reason, plan and use tools. The interesting work is no longer "can we get the model to do this" — it is "should we, for whom, with what guardrails, at what cost?"
KiteLabs is a studio for that second question. Small apps with a clear user, narrow scope and the discipline to evaluate honestly before we ship.
We pick problems where applied AI removes a specific tax on someone's day — paperwork for clinicians, drilling for learners, rewriting for jobseekers, reading filings for investors. Each app is one job, done well.
Operating principles.
Six things we keep coming back to when the temptation is to over-build.
One job per app
If we cannot describe the app in one sentence, we have not finished thinking about it. Apps with one job get used. The rest get demoed.
Retrieval over recall
Ground the model in the user's data, the right reading list, the right tools. Don't let it freelance.
Evals are the product
Trace every call, regress against golden sets, watch silent drift. If we cannot measure quality, we don't ship.
Flags everywhere
Every AI feature ships behind a flag and a kill switch. The off button has saved us more than once.
Costs in the loop
Model cost and latency are first-class metrics. We route to the smallest model that holds up.
Boring infra
The frontier sits on top of a stack so dull it is almost embarrassing. That is by design.
Multiple apps, one team.
We run several apps off a shared platform — one retrieval layer, one eval harness, one set of guardrails. That keeps overhead low and lets the team move between apps as the work demands.
Each app has its own roadmap, its own users and its own success metrics. The platform underneath is invisible to them — the way good infrastructure is supposed to be.
If you are a partner, an early user or someone with a problem worth an AI app, get in touch.
Independent, India-based, building in the open.
Self-funded. Small. Working in public via the blog and the lab notes. Take a look at what is on the bench, or talk to us about what should be.