AI Agent Development
An AI agent is a system that decides which steps to take and calls your tools to take them, rather than producing text for a person to act on. That makes it useful for multi-step work and risky in exactly the same measure — an agent with write access can do real damage quickly. We build agents with narrow permissions, full audit trails, and human confirmation on anything expensive or irreversible.
Where agents genuinely earn their place
Agents suit work with a clear goal, several steps, and tolerance for a retry. They suit high-volume, zero-tolerance transaction processing far less.
- Triage and routing: read an incoming item, classify it, act or escalate.
- Research and summarisation across several internal systems.
- Multi-step back-office work that currently means a person copying between tools.
- Drafting that a human reviews and approves before anything is sent.
Permissions and blast radius
The design question is not what the agent can do when it works, but what it can do when it is wrong. We answer that before building anything.
- Least-privilege tool access — read-only by default, write granted case by case.
- Explicit human confirmation for spending, sending, or deleting.
- Rate and budget limits per run, so a loop cannot become an invoice.
- A full trace of every step, so any action can be explained afterwards.
Making agents testable
An agent that behaves differently every run is not something you can maintain. We pin down what can be pinned: deterministic tools with their own tests, recorded traces replayed as regression cases, and evaluation over whole runs rather than single responses. Without that, every change is a gamble and nobody will trust the system enough to widen its permissions.
Frequently asked questions
- How is an agent different from a chatbot?
- A chatbot produces text for a person to act on. An agent takes the actions itself by calling tools — querying a database, opening a ticket, sending a message. That difference is why permissions and audit trails matter far more than they do for a chat interface.
- What if the agent does something wrong?
- Assume it will, and design so the consequences are bounded. Irreversible and expensive actions sit behind human confirmation, tool access is minimal, and every step is logged in enough detail to reconstruct and reverse what happened.
- Can it work with our existing tools?
- Yes — agents act through whatever APIs you already have. Where a system has no API, the same file, queue, or database routes we use for conventional integration apply.
- Is this worth doing yet?
- For bounded, reviewable work, often yes. For unattended, high-stakes, high-volume processing, usually not yet. We would rather tell you that than build something you have to turn off in a month.
Tell us what you are building
Send a short description of the system and the constraint you are hitting. We reply within one business day.
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