guide · deployment

Deploy an AI agent. From scoping to production.

Many AI projects stall between POC and production. Here's the method to cross over: rigorous scoping, iterative build, supervised go-live.

success conditions

Four conditions to validate before build.

Engaged business sponsor: not an isolated IT project, a business-driven one.

Measurable flow: you can quantify before/after, otherwise no provable ROI.

Accessible data: minimum quality, clarified access rights.

Production plan: not just a POC, an industrialization path.

6 deployment steps

Flow audit, KPI identification, scope definition. Short but critical.

Architecture, integrations, supervision rules, test plan. Written before build.

Agent design, integrations, supervision setup. Short cycles, regular review.

Functional, security, compliance, accessibility testing. Not optional.

Progressive deployment, active monitoring, user training.

Continuous measurement, adjustments, updates. The project lives after go-live.

What we get asked before starting

With scoping: targeted flow, identified sponsor, mobilizable data, defined KPIs. Not with the model choice.

Bounded pilot: weeks. Multi-flow integrated system: months. Timing depends on complexity.

Define before build: expected ROI, KPIs, engaged sponsor, production plan. Without this, the POC stays a demo.

Business sponsor, IT, compliance, user team. If one is missing, the project stalls sooner or later.

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