I build small AI agents for jobs that have a clear starting point and a clear output. One example is reading an incoming request, checking it against information you provide, and drafting the next action for a person to approve. Another is sorting records that need attention and explaining why they were flagged.

We will choose one workflow before development starts. The goal is to see whether the agent can do useful work with your real examples and to identify where a person should stay in control.

A short workflow map showing the trigger, information the agent can use, its output, and the point where a person reviews uncertain results.

A working pilot with one trigger, one source of information, and one output or action.

Tests using examples you provide, including cases where the input is missing or unclear.

Setup notes and a walkthrough of what the pilot does and where it needs improvement.

For a pilot, I prefer to keep consequential actions behind human approval. That makes it easier to test the workflow without pretending the agent can safely handle every edge case on its own.

You will provide examples of the task, the rules your team follows today, and access to any system the pilot needs to use. If an integration is involved, we will confirm that its API and test access are available before agreeing on the scope.

This starting package is for one workflow. It does not include a custom dashboard, several integrations, unattended operation across your business, or ongoing hosting and model usage. A production rollout can be planned after the pilot shows what works.

Can the agent take action automatically? The pilot can prepare an action. Whether it should execute that action without approval depends on the risk, the systems involved, and the test results.

Can we add more workflows later? Yes. We can use what we learn from the first one to scope the next workflow separately.