“A repetitive task follows rules we could write down, but a person still does it by hand.”
We build AI assistants for defined work, with your people setting the rules and approving what matters.
Sound familiar?
The knot.
Your team wastes hours on repetitive work a machine should handle.
There's work that needs doing but it's repetitive, tedious, and eats time your team should spend on real work. You're stretched thin, your team is stretched thin, and the answer isn't just "work harder." But off-the-shelf AI feels risky without the right controls in place.
Three signs it’s this
- 01 The task follows rules you could write down on one page.
- 02 Skilled people spend hours on it that they could spend on judgement work.
- 03 Mistakes happen because it is repetitive, not because it is hard.
T40 answer · Custom AI Agents
The fix.
We build AI agents that handle the work - research, drafting, data processing, customer responses. Not generic chatbots, but agents trained on your business, your processes, your voice. Capacity without headcount. Work gets done without burning out your team.
After An assistant for that defined job, with your people setting the rules and approving what matters.
What you get.
The deliverables, plainly listed. If it's not here, ask — we'll tell you honestly whether it's included.
- 01 Custom AI agents trained on your business, terminology, and processes
- 02 Research agents that gather and synthesise information automatically
- 03 Content drafting agents for emails, reports, and documentation
- 04 Customer service agents that handle enquiries in your voice
- 05 Data processing agents that extract, transform, and analyse information
- 06 Integration with your existing tools so agents work within your workflow
How this one works.
No discovery phases that outlive the project. Just the steps that earn their place.
- 01 Use Case Definition We identify exactly what the AI agent needs to do - the tasks, the inputs, the outputs, the quality standards. Clarity upfront prevents disappointment later.
- 02 Agent Design We design the agent architecture - which AI models to use, what knowledge to include, how to handle edge cases and errors.
- 03 Training & Testing We train the agent on your business context and test extensively. Real scenarios, real data, real quality standards. The agent earns its place before deployment.
- 04 Deployment & Iteration We deploy the agent into your workflow and iterate based on real usage. AI agents improve over time - the first version is the starting point, not the end.
Why this matters
AI agents represent a fundamental shift in what is possible for small teams. Tasks that previously required dedicated staff - research, content creation, data processing - can now be handled by AI that works 24/7, never gets sick, and costs a fraction of salary. The competitive implications are enormous.
Who this suits
- Small teams with more work than capacity to handle it
- Businesses with repetitive tasks that consume skilled staff time
- Companies that need 24/7 capability without 24/7 staffing
- Leaders who want to scale output without scaling headcount proportionally
When we would advise against it
- Every case needs a fresh judgement call. An agent would need so much checking it saves nothing.
- There is no one to approve what the agent does. We build with a named human owner, or not at all.
The questions everyone asks.
If yours isn't here, ask it — we answer emails within 24 hours.
Q1 How good are AI agents compared to humans?
For well-defined, repetitive tasks - often better. Faster, more consistent, never tired. For tasks requiring judgment, creativity, or relationship - humans still win. We help identify which is which.
Q2 Will the agent sound like a robot?
Not if built properly. We train agents on your actual communications, terminology, and tone. Customers often cannot tell they are interacting with AI. Quality depends on training quality.
Q3 What if the agent makes mistakes?
All AI makes mistakes sometimes. We design for this - human review workflows, confidence thresholds, escalation paths. The goal is augmentation, not blind automation.
Q4 How much does a custom AI agent cost?
Typically £10-30K for development depending on complexity, plus ongoing costs for AI model usage (usually £100-500/month for moderate usage). We compare that with the measured cost of doing the work by hand before you commit.
Sound like your problem?
Tell us where it hurts. We’ll tell you honestly whether we can help — and what we’d do first.
First paid step · T40 Systems: Systems Diagnosis · £750