Custom AI agents for defined business workflows
Scope an AI agent around a real task, reliable knowledge and controlled access. Test its decisions, exceptions and handovers before a pilot.
Choose the task before the model
Start with the work: what arrives, what decision is needed, what information supports it and what a successful output looks like. Some tasks need a simple rule or integration. Others benefit from language understanding.
Give the agent a clear job
Examples include preparing account research, drafting a response from approved knowledge or checking whether an order file has the information needed for the next department. Each needs a named owner and a defined stopping point.
Design the action boundaries
List read access, proposed changes and actions requiring approval. Provide a human fallback when information is missing or the task falls outside scope. Credentials and access rights belong in the implementation design, not in a prompt pasted into a chat.
The pilot package
Agree the workflow specification, integration plan, representative test cases, review interface, operational logs, documentation and recovery procedure. Provider costs, support and ongoing evaluation are scoped separately.
Evidence before expansion
Compare the pilot with the current process using task correctness, exception handling, reviewer effort, elapsed time and cost per completed task. A convincing demonstration is not evidence that production permissions, reliability or business impact have been validated.
Bring us the business question
Tell us what should work better, which systems you use and who needs to work with them.