AI agent development
Hand a repetitive, rule-based workflow to an AI agent that calls tools, works through the steps and keeps a record. Where a person needs to make the call, it stops.
01
Who it’s for
- Your processes are fixed but have many steps, such as compiling quotes, checking orders or assembling reports
- You’ve tried a chatbot, but what you need is something that does the work, not just answers
- Work involves copying and pasting back and forth between several systems
- You want to try one workflow first and expand once it works
02
What we do
Process analysis
We break down each step of the current process and find the points that need human judgment and can’t be handed to AI.
Agent design
We define its role, the tools it may use, when it stops, and when it hands back to a person.
Development and tool integration
Built on models such as Claude and Gemini, with tools provided over MCP, so switching models later doesn’t mean rewriting the integrations.
Testing and evaluation
We test accuracy on real cases and list the known failure modes and how each is handled.
Launch and monitoring
Every action is logged, the person responsible is notified when something goes wrong, and results are reviewed regularly.
03
How it works
1. Process analysis
Pick one workflow and record how it’s done today, how long it takes and where mistakes happen most.
2. Design and spec
Write down what the agent does, what it doesn’t, and when it stops.
3. Build and test
Build it and test it repeatedly against real cases.
4. Pilot and launch
Let a few staff use it first, then launch it and hand over how it is monitored.
04
Deliverables
- Process analysis and agent design document
- Agent code, prompts and tool configuration
- Test cases and evaluation results
- Launch, logging and alert configuration
- Maintenance documentation
05
Engagement cycle
Each cycle runs three months, six months or a year, depending on scope. At the end of each cycle we sit down with you and compare the results against the goals set at the start, then decide what the next cycle should cover, or whether to stop there.
Every cycle: audit → design → implement → check against the goals, then decide what's next
06
Pricing
Each engagement is estimated on its own: how many systems and how much data are involved, the people and time needed, and how long the cycle runs. Talk to us first and we’ll give you a number based on the actual scope, rather than quoting a price and then fitting the scope to it.
07
Common questions
How is an AI agent different from a chatbot?
What if the AI agent gets something wrong?
Are we locked into one AI company’s models?
08
Further reading
Tell us where you are
Email us about where you’re stuck, and we’ll reply with what could work and the next step.