AI MVP development

Typically six to twelve weeks for a focused MVP with one core AI feature, authentication, billing and analytics. The variables are the number of integrations, the novelty of the AI component and how much design is needed. We scope to what you must learn from users, not to a feature list.

It depends on how much model usage each user drives. We model cost per user during architecture, design pricing and limits around it, and build metering so you see margins from launch. Caching, smaller models and batching keep the number down. Usage-based limits and fair-use policies are designed into plans, so a handful of heavy users cannot make the product unprofitable.

Either. We can own the full stack (frontend, backend, AI, infrastructure) or embed alongside your engineers to deliver the AI features. Most early-stage clients want the full team; most established SaaS companies want targeted features. In both cases you get a named team, a shared backlog and weekly demos, so there are no surprises about what is being built.

You do. All code, prompts, models and documentation are delivered into your repositories and accounts under your ownership. We use open-source and standard tools so you are never locked in to us. Contracts state this plainly, and code lives in your repositories from day one rather than being handed over at the end.