Big Immersive

Applied AI products

Shipping AI into products people pay for, rather than demos that impress in a meeting.

01What this means

Most AI work dies between the notebook and production. This is the discipline of the other half: retrieval that stays correct as the corpus grows, prompts versioned like code, model calls that degrade rather than fail, and an evaluation loop that tells you the day quality drops instead of the week a customer does. The studio has taken this route end to end on live consumer and enterprise products.

How we approach it

The recurring failure in applied AI is not model quality, it is scope. A model asked to reason about everything gives fluent, confident, unfalsifiable answers; a model scoped to a named body of knowledge can be checked. That is the choice behind every AI product here — a contract analyser bound to specific named legal instruments rather than to law in general, a decision engine that returns a fixed shape with the counter-argument attached, a children's platform where safety is a property of what the model can reach rather than a filter on what it says. Narrowing is the engineering.

Stack

Python · FastAPI · TypeScript · Next.js · PostgreSQL · Redis · Celery · Vector search · Streaming (SSE/WebSocket)

02Evidence3 projects