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Your first AI agent in 30 days

A four-week plan for teams that already know which process to start with.

Week 1 — map the operation

Choose one frequent workflow. Capture volume, processing time, errors, dropped items and ownership. Collect real examples, including exceptions.

Deliverable: current-state map, baseline and data inventory.

Week 2 — build the controlled agent loop

Define the sequence: receive an event, read approved data, apply rules, prepare a decision, request approval where required, act and log evidence.

Classify permissions as autonomous, approval-required or prohibited.

Deliverable: a test workflow running on copied or sandboxed data.

Week 3 — limited production exposure

Connect one channel and a small share of traffic. Compare agent decisions with a responsible employee. Fix explicit rules around exceptions rather than hiding failures inside a longer prompt.

Deliverable: action log, known limitations and a tested stop procedure.

Week 4 — prove the economics

Compare like-for-like periods:

• time to first action;
• completion rate;
• error rate;
• manual hours;
• cash actually recovered or saved;
• decisions still requiring a person.

Deliverable: stop, improve or scale decision.

Minimum operating architecture

event → source of truth → agent → rules → human approval → action → evidence → metric

Without a source of truth, evidence log and stop mechanism, an agent is a demo, not an operating capability.

Good first workflows

Lead qualification, stalled CRM opportunities, invoice-document reconciliation, document extraction, management reporting, service-ticket routing and deadline control are often suitable because they are frequent and measurable.

Next step

Evolvin scopes a pilot around one metric, connects the required systems and keeps critical decisions human. Once the outcome is proven, the agent can connect to adjacent workflows.

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This material is a method, not a promise of a result. Any figure in your case is measured before and after — not assumed.