Most AI engagements start with a model. Ours starts with a map. Before we architect a single agent, we trace the workflow end-to-end - the requests, approvals, handoffs, exceptions, and bottlenecks. The output is a working operational map and a scoped build target your team can defend.

The audit gave us a build target. This phase turns it into a system design. Model selection, data flow, integration architecture, escalation paths, rollback triggers, and the redesigned workflow your team will actually use. Every decision documented. Every trade-off surfaced. No code gets written until the design is signed off.

This is where most AI projects die. The build looks great in a sandbox, then collapses on real data and real load. Rozeta builds against your production environment from day one. Real data, real APIs, real volume, real change management. By the time the agent ships, it's already been tested under the conditions that actually matter.

Most AI agents peak the day they ship. Ours don't. After launch, we monitor real performance against the metric the agent was scoped against, retrain on production data, and refine the system every quarter. The end goal isn't an agent that depends on us. It's an agent your team owns and runs without us.