AI Agent Development
We build AI agents that do the work, not just answer questions: they read, decide, use your tools and hand back a finished result.
An agent is given a goal, the tools it may use and the rules it must follow.
We design each one around a real job, such as qualifying leads, processing documents, handling support tickets or preparing reports, and give it access only to what that job needs.
Every agent ships with guardrails, logs and a human approval step wherever a mistake would be costly, so your team can see what it did and why. We start with one agent and one workflow, measure it, then expand.
How an agent does the job
Give it a job
An agent starts with a clear goal, such as qualifying a new lead, then plans the steps, does them and reports back with a finished result instead of a draft.
- Task agentsAgents that complete multi-step jobs end to end: research, fill forms, update records and send the result.
- Read the enquiry and company website
- Score against your ideal-customer rules
- Create the deal and notes in the CRM
- Book a call in the sales calendarNeeds approval
Connect your tools
Agents work inside the software you already use. We give each one access to only the tools its job needs, with its own account and permissions.
- Tool use & integrationsAgents connected to your CRM, email, calendar, database and internal APIs with scoped permissions.
- Gmail
- Slack
- HubSpot
- Salesforce
- Sheets
- QuickBooks
Agents that work as a team
Bigger jobs are split between agents with one role each, which hand work to one another, like a researcher, a writer and a reviewer preparing a report.
- Multi-agent workflowsSeveral specialised agents that hand work to each other, with a supervisor checking quality.
- Research agentGathers news, prices and competitor moves
- Analyst agentFinds what changed and why it matters
- Writer agentDrafts a two-page summary
- Reviewer agentChecks facts and sources
- Sent to your team on Monday
People stay in control
You decide what an agent may do on its own and what needs a person's yes. Every step is logged, so you can always see what it did and why.
- Guardrails & oversightApproval steps, activity logs and limits so people stay in control of what agents can do.
How we work
- Week 1Pick the jobWe choose one real task, write down how your team does it today and agree what a good result looks like.
- Weeks 2–3First working agentA first version runs on real examples in a safe test space, so you can see its work before it touches live systems.
- Weeks 3–6Connect and limitWe connect your tools with the narrowest permissions possible, and set which actions need approval.
- LaunchSupervised startThe agent starts with a person reviewing its work, and takes on more as it proves reliable.
- Every monthReview and extendWe review its logs and results with you, fix what it gets wrong and add the next job.
Our products and client work for AI Agent Development
All productsQuestions
What's the difference between a chatbot and an agent?
A chatbot answers questions. An agent gets a goal and the tools to reach it: it plans the steps, uses your software and hands back a finished piece of work.
Can an agent make mistakes?
Yes, so we design for it: narrow permissions, approval steps for anything costly, full activity logs, and testing on real examples before and after launch.
Which AI models do you use?
We pick per job from models such as Claude, GPT and Gemini, or open-source models you can host yourself, based on accuracy, speed and cost.
Do agents replace our staff?
They take over the repetitive steps so your people spend their time on customers, judgement calls and the work agents can't do.
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