Systems review
We look at the work as it happens, with the people doing it, and agree what is worth fixing first.

Some tasks need more than a fixed rule. We can design agents that research, monitor, triage or move information between systems, with clear limits and approval points.
THE PROBLEM
WHAT WE CAN SHIP
IN PLAIN TERMS
An agent is a supervised AI process that works through several steps towards a goal. It checks sources, gathers information, drafts output or moves records between systems, and it decides what to do next along the way.
Agents are worth building when the task is repeatable, the goal is clear and someone can review the result. They are a poor fit where the rules change constantly, or where a mistake would be expensive and hard to spot.
CHOOSING A ROUTE
Agents are the most powerful option and the easiest to over-apply. This is the order we test them in.
| Route | Best when | Watch out for |
|---|---|---|
| Fixed automation | The steps are known in advance and the same every time. | It cannot handle exceptions or judgement. |
| An AI step in a workflow | One decision needs reading or judgement, then the process continues. | It handles one decision, not a chain of them. |
| A supervised agent | The work spans several steps, sources or systems and follows a repeatable pattern. | It needs clear limits, logging, and a person who owns the outcome. |
HOW IT USUALLY RUNS
We look at the work as it happens, with the people doing it, and agree what is worth fixing first.
A focused build lands in two to four weeks. You see it working before we plan the next step.
The same developer handles the changes, the integrations and the questions after launch.
WHAT GOES WRONG
BEST FIT
Businesses with a defined process, a clear owner and a reason to automate beyond a simple API workflow. Complex agent work starts with discovery.
QUESTIONS WE GET ASKED
Automation follows steps you define in advance. An agent decides its own next step within limits you set. Use automation when the path is known, and an agent when the work needs judgement across several steps.
Limits are agreed before the build: what it can access, what it can change, what needs approval, and when it must hand back to a person. Every run is logged.
Not for anything that matters. Most projects run with a human approval point at the step where a mistake would be costly. Full autonomy only makes sense where errors are cheap and reversible.
Repetitive research and monitoring, triaging incoming requests, and moving information between systems with no clean integration, especially older browser-based tools.
With one task, one owner and one measure. If a supervised agent beats the current process on that task, it earns a wider role.
We will sit with the people doing the work, map the handoff, and tell you what is worth fixing first.
Book a systems review