AI Agents
Custom AI Agent Development:Agents that know your business, not the internet
A general chatbot can't answer a question about your pricing, your stock or your policies — and it will invent an answer rather than admit that. An agent grounded in your own data and wired into your own systems answers from what's true, and is tested so you know when it stops.
Retrieval over your data · Tool use · Guardrails and evals · Cost and latency tuning
The problem
Most AI assistants fail for the same four reasons
It doesn't know anything about you
Out of the box it knows the public internet. It doesn't know your SKUs, your lead times, or what you told this customer last month.
It can read but it can't act
Answering the question is half the job. The useful version checks the order, updates the record and sends the confirmation.
It makes things up, confidently
Without grounding and guardrails it will invent a policy, a price or a delivery date — in your brand voice, to your customer.
Nobody can tell when it gets worse
A prompt change or a model update quietly degrades the answers, and you find out about it from a complaint.
What you get
What's included
Scoped tightly on purpose. An agent that does four things reliably is worth more than one that attempts forty and is trusted for none of them.
Retrieval over your own knowledge base
Your documents, tickets, product data and past conversations, indexed so answers come from your material — with the source attached to the answer.
Tool use wired into real systems
Look up an order, check availability, raise a ticket, update a record. Scoped tightly to what the agent is allowed to touch.
Guardrails on what it can say and do
Explicit boundaries on topics, claims and actions, with anything consequential routed to a person instead.
An evaluation suite
Real questions with expected answers, run on every change, so a regression shows up in your tests rather than in your inbox.
Cost and latency tuning
The right model for each step rather than the largest one everywhere, with caching and fallbacks. Usually the difference between a demo and something you can afford to run.
Deployment and handover
Running in your infrastructure, with the prompts, evaluations and documentation in your own repository.
Working together
Clear decisions from brief to handover
The same three steps on every project, whichever service you start with. You know the scope and the fee before any work begins.
Find the workflow worth fixing first
I map how the work happens today, keep what already works, and pick the highest-leverage fix. You get the deliverables and a fixed fee in writing before anything starts.
Review it working, on your own tools
You test a working prototype connected to your real systems, with a person approving anything that reaches a customer, while changes are still cheap.
Ship it and hand over the keys
I deploy into your accounts with logging and alerts, document it, and walk your team through it. You own the code, prompts and infrastructure from day one.
A few useful answers
Before we start
Still have a question? Book a call and we can talk it through and agree the right next step.
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Tell me what needs to change
Share your product and the work you need. I'll help you find the right scope and next step.