Custom AI agent development, built around your work

What an agent does that a chatbot does not

An agent is software that orders its own steps towards a goal and uses tools along the way. A chatbot writes an answer and stops. An agent carries the job further.

Take one request: “Find this week’s overdue invoices and draft a reminder for each customer.” The agent opens your accounting records, pulls the list and writes a separate draft for every customer. Then it stops and shows you the drafts. Sending them is your call.

The work an agent can take on

Agents do best on work that repeats often and follows clear rules.

• Research: scans sources on a topic you set and gathers the findings, with references, in one note.
• Decision prep: compares quotes, suppliers or candidates against your criteria and writes down its reasoning.
• Document work: reads contracts, invoices and forms, extracts what you need and flags gaps or contradictions.
• Operations: watches orders, stock or support tickets and alerts the right person when something breaks a rule.
• Record keeping: turns meeting notes into tasks and enters them in your CRM or project tool.

How the build goes

We work in four steps. First we listen: who does the job today and where they get stuck. We suggest starting with one workflow, because a small agent is easier to measure.

The second step is design. We put in writing which data the agent can reach, which tools it uses and where it must stop. No code is written until you approve that document.

During development we give the agent a set of jobs you have already done by hand and put its output next to yours. At handover you receive a working agent, followed by round-the-clock technical support and consulting.

Permissions, approval and logs

An agent can misread a request or guess when information is missing. So every agent gets narrow permissions and reaches only the systems its job needs.

Steps that are hard to undo, such as moving money or deleting records, wait for a person to approve them. Every step is logged. If a result looks odd, the log shows which data the agent read and why it decided as it did.

Which model, and where it runs

We are not tied to one AI model. Depending on the job we choose a commercial cloud model or an open-source model running on your own hardware. With sensitive data the second route is often better, because the data stays in your environment.

The agent can run on your own computer, your own server or in the cloud.

Choosing an AI agent development company

Ask any AI agent development company three questions. Can they show you how the agent failed in testing? Will it still work if the model behind it is replaced? Who looks after it once it is live?

We will also tell you when an agent is the wrong tool. A task whose steps never change is cheaper and more predictable as plain automation. A task nobody can describe clearly has to be written down before any agent can do it.