AI agents
AI coworkers that answer enquiries, qualify leads and take on the tasks that would otherwise sit waiting for a person.
An AI agent is not a chatbot on the front page. It is a colleague without an employment contract: it has access to your systems, it has a bounded job, and it does that job every day without anyone having to remember it.
We build agents for the work that is too dull for a person and too unpredictable for a spreadsheet. It usually starts with one task, and once that runs, you find the next three yourself.
Assessing the task
We walk through the workflow and work out whether the task suits an agent at all. Some jobs are better solved with a simple automation, and we say so.
Access and boundaries
What the agent may see, what it may change, and where it has to ask a person. The limits are set before we build, not afterwards.
A trial run on your data
We run the agent against real cases from your own archive and show you what it would have answered, before it answers anyone.
Enquiries and support
The agent reads incoming mail or messages, answers what it can, and passes the rest on with a summary and a suggested reply.
Work across systems
The agent can read and write data in the systems you already use — CRM, commerce platform, spreadsheets, ad accounts — so it does not just talk, it acts.
Monitoring and alerts
The agent watches what you would otherwise check yourself, and speaks up when something looks wrong. Not a weekly report, but a message when it matters.
Start by letting it propose, not act
The fastest route to an agent you trust is to let it write the draft while a person presses send. You get the benefit immediately, you can see how often it lands correctly, and you decide when it may be let loose on which parts. Where a mistake is expensive, the approval step stays permanently.
See what it costsHow we deliver
The same approach whatever the area. You can stop after each phase, and you know what the next step costs before agreeing to it.
We map it out first
Ninety minutes going through your processes to work out what can genuinely be automated. You get a clear picture of what is possible and what it would cost.
We build on a fixed price
One- to two-week sprints, each ending in a demo. You know the cost before we start, and you own the code afterwards. No lock-in, no long contract.
We keep it running
Service plans covering maintenance, support and extensions as the business changes.
Is this the right place to start?
If two or more of these sound familiar, there is usually something to gain. If none do, we would rather say so now than after a proposal.
- Someone spends the first hour of every day on the same thing
- Enquiries sit unanswered because nobody gets to them
- The task needs judgement, so a spreadsheet or a simple rule is not enough
- You could describe the work precisely enough to train a new hire
Questions we get asked
What if the agent gets it wrong?+
We always start by letting the agent propose rather than act. It writes the draft, a person approves. Once you can see it lands correctly over time, we let it run on the parts where a mistake is survivable. Where a mistake is expensive, the approval step stays.
Which model do you use?+
Whichever fits the job. Some tasks need a large cloud model, others run fine locally on your own machine. We choose on task, cost and where your data is allowed to sit — not on what is newest.
What does it cost to run afterwards?+
There are two items: usage at the model provider, which depends on volume, and any service plan with us. We work out both before you say yes, so you know the running cost and not just the build price.
Can our staff see what it is doing?+
Yes. Everything the agent does is logged in a format a person can read — what came in, what it decided, what it did. Without that you can neither debug it nor trust it.