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How it works

From a prompt to production, governed the whole way

Sapilon is a path, not a one-shot generation. Every project moves through four stages, and each stage keeps the AI constrained, observable, and reversible.

An orchestra rehearsing on a wooden stage, every musician following a conductor at the podium
  1. 01

    Design

    See the new system before any backend exists.

    A 10-minute guided interview learns your software: size, stack, team, and intent. The questions are about your software, not about us. Sapilon then proposes an opinionated, AI-safe architecture and a migration roadmap, and builds the new frontend with mocked data. You validate the experience first, before any backend work starts.

  2. 02

    Build

    The governed agent wires it up end-to-end.

    The backend, database, and APIs are generated against best-practice, periodically updated templates. The app runs end-to-end on your Build Server, a real development environment. Every AI action is logged, diffable, and reversible, inside explicit ownership zones that define what the AI may touch and what stays under human control.

  3. 03

    Rehearsal

    A full dress rehearsal before anything goes live.

    The system is deployed to a pre-production Rehearsal Server in your own AWS. Real user journeys are walked through, every change passes automated code review with a full audit trail, and the data migration is drilled until it is routine. Security and costs are checked, so go-live holds no surprises.

  4. 04

    Live

    Real users, real data, built to last years.

    The new system takes over on your Live Server and the old one is retired. Versioning, upgrade-aware diffs, monitoring, and backups keep the software healthy for years. You keep plain Git, open libraries, and your own AWS account, with cost visibility and no lock-in.

See the four stages on your own software

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