Custom AI Agents
Build an assistant that can interpret a request, choose from approved tools and prepare an action for review. We define the agent’s task, permissions and stopping conditions before connecting it to business systems.
Service scope
Use this service when a task involves interpreting a request and choosing between several permitted actions. We design the agent around a specific outcome, the systems it can use and the point where a person should take over.
Describe what the agent should achieve, the context it needs and what a completed task looks like. Decide when it should ask a question, stop or hand the work to an employee.
We agree representative tasks and difficult cases before building, rather than giving the agent an open-ended instruction to run the business.
Connect selected functions such as finding a customer record, reading a request or preparing a draft. Validate tool inputs and outputs and limit the records and actions each connection can reach.
Actions such as sending a message or updating a live record follow the approval rules agreed for that task.
Test the agent’s decisions across representative requests, missing information and tool failures. Review both the final result and the actions it took to reach it.
Include execution history, time and usage limits, and a way for an operator to interrupt or take over a task.
Illustrative project examples. The work included is agreed for your project.
An agent reads a new request, looks up permitted account information and prepares a proposed next step. An employee reviews the recommendation before any agreed consequential action.
An agent gathers context from approved internal systems, identifies missing information and prepares a response draft. It hands uncertain cases back to the team with the evidence it used.
What you receive
The written proposal defines the deliverables and acceptance checks for your engagement. A typical implementation includes the following.
The task boundary, permitted tools, access rules, approval points and stopping conditions.
The agreed agent logic and tool connections, plus a way to review its proposed work and execution history.
Representative tasks with expected outcomes, tool-use checks and failure scenarios, including cases that should stop or escalate.
Instructions for running, reviewing and stopping tasks, usage limits and ownership of future model or tool changes.
Bring examples of the task, the decisions a person makes today and the software they use. We check whether suitable interfaces and permissions exist before promising a tool connection.
Approval requirements are part of the scope. We identify actions that may run automatically and those that must wait for a person.
Where suitable interfaces and permissions exist. We confirm access, licensing and operational constraints before committing to an integration.
Use agreed examples, expected tool calls and stopping conditions. We examine incorrect actions and exception handling alongside successful tasks.
Related services: Internal AI Knowledge Assistants AI Integration & Support
Read how we work and about the team. Cloud architecture is a supporting delivery capability.
Tell us about the work, the people involved and the outcome you need. We will agree an appropriate next step.
Discuss your project