Custom AI Agent

The problem

Your teams often answer the same questions and search for information across scattered documents. A generic assistant knows neither your business nor your boundaries. I design an agent around a specific use case, with authorized sources, permitted actions, and situations that must be referred to a person.

This is for you if…

• The same questions come up every week.
• Finding information requires consulting several documents.
• You want to use AI with a clear scope and clear rules.

What changes

How it runs

1. 01

   Choose a concrete use case

   We define the users, the requests to be handled, and the criteria that will be used to assess the agent’s usefulness.

2. 02

   Prepare the sources and boundaries

   We select the relevant documents and access permissions. The authorized actions and cases requiring validation are defined.

3. 03

   Test with real-world cases

   I build an initial agent and measure its responses on representative examples, including ambiguous or out-of-scope requests.

4. 04

   Deploy and adjust

   The agent is integrated into the intended workflow. We monitor its limitations and adjust its sources and instructions.

The questions I get asked

• Can the agent make mistakes?

  Yes. We plan for testing, limits, and human oversight. For sensitive use cases, its responses remain suggestions to be verified.

• What data does it need?

  Only the information necessary for the use case. Providers’ sources, access, and processing conditions are reviewed during scoping.

• Can it act in my tools?

  If the tools allow it and if it meets the need. Actions are limited to the agreed scope, with validation when necessary.

• What cost should be expected?

  The quote distinguishes implementation from any recurring costs of the services used. Usage volume and integrations influence the budget.