Where the work gets stuck.
An AI model can give a useful answer and still be unsafe when it acts on its own. Real work needs permissions, evidence, rules for when to stop, approval steps, and a record of what happened.
SERVICE.02 — AI AGENTS
Give an AI agent one job, clear limits, and a record of every action.
An AI agent is software that uses an AI model to do a task in your other systems. We build each one for a defined job, with limited access, not as an open chat tool that can reach everything.
Start with the business problem, not the type of software.
The right solution becomes clear once we can see the records, handoffs, decisions and the cost of mistakes.
What the system changes.
The agent handles one defined task, uses only the systems you approve, records each important step, and stops when it lacks the information or permission to continue.
Every part supports one process.
Each screen and connection has a clear role in the process, so the system stays easy to understand as it grows.
Limited access
Limit each agent to the systems, actions, data and spending its job needs.
Human approval
By default, a person approves before anything is sent, paid or changed in your records. You can choose to automate specific low-risk steps, such as routine reminders, agreed in writing.
Records and testing
Record what came in, what the agent did and what it produced. Then test important behavior on a maintained set of real cases.
Safe handling of failures
Reject output in the wrong format, pause when the evidence is weak, and follow a set recovery step when a connected system fails.
One complete process before more automation.
The first release covers one process from start to finish. New cases and permissions come after that first version works well.
- 01 — JOB
Define one useful job.
Set what starts the job, the allowed inputs, the expected result, and the exact point where the agent stops.
- 02 — LIMITS
Build the safety checks.
Add access limits, format checks, rules, records, review steps and failure handling around the AI model.
- 03 — TEST
Expand only after testing.
Run real cases in draft mode, where a person reviews every proposed action, before the agent gets more permissions.
See related projects.
These pages show delivered systems or explain how we build, without showing private client rules or data.
Engineering approach
See how we limit and record an AI agent.
The engineering page explains the rules, access limits, records and tests we put around an AI model.
Open the page Representative patternSee how an agent fits into a business system.
The Work page shows where permissions, review steps and status fit around an automated task.
Open the pageQuestions to answer before we build.
These are useful questions to settle before design or development starts.
What makes an AI agent different from a chatbot?
A chatbot only answers. An agent can use other software and change your records. That is why it needs stricter permissions, a record of each action, review, and clear rules for when to stop.
Can every action be reviewed at the start?
Yes. In draft mode the agent proposes actions and a person decides. Your team can compare its proposals with their own decisions before giving it more permissions.
Can the system refuse to act?
Yes. When it is unsure, lacks evidence, finds a rule conflict or cannot reach a connected system, it stops and passes the case to a person.
NEXT — YOUR PROCESS
Tell us about one process that needs fixing.
Describe what starts it, the people involved, the current handoffs, and the result you need to rely on.