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AI 500 · AI

AI Agent Development Manchester

An AI agent does more than chat. It takes a task, decides which tools to use, and works through the steps, such as searching your CRM, drafting a quote, updating a spreadsheet and preparing an email. We build agents for Manchester businesses that start with one narrow, well-defined job and keep a person in charge.

  • Since 2003trading in Manchester
  • 20,000+UK businesses helped
  • Collect M8Unit 3, 116 Bury New Road
  • A personchecks every file
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AI 500

Automation and agents

Every job is a fixed quote, agreed in writing before any work starts. No obligation.

All 20 AI servicesOr tell us what you need and we will quote it.Talk about AI

What makes an agent different

A chatbot answers a question and stops. An agent is given tools, each one a specific action it is allowed to take, and it chains them together to finish a task. Asked to prepare a quote, it might look up the customer, check past orders, apply your pricing rules and leave a draft for a salesperson.

That is also where the risk lies. Language models misread instructions, pick the wrong record or loop on a failing step. So we design agents the way you would brief a new member of staff: clear job, minimal access, sign-off for anything important, and a record of everything they did.

Where a task follows the same fixed steps every time, a plain workflow is often better than an agent, and our AI automation page covers that. Agents earn their place when the steps vary with each case.

Jobs agents suit well

The best first agent handles a task your team does often, by hand, across several systems.

  • Sales teams preparing quotes and follow-up emails after pulling details out of a CRM.
  • Recruitment firms matching new CVs against open roles and drafting shortlists for a consultant.
  • Property managers turning tenant repair reports into contractor job sheets.
  • Accounts teams chasing overdue invoices with drafted reminders for approval.

How we build an agent

1

Pick one narrow job

We choose a single task with a clear start, finish and owner.

2

Define the tools

We list each action the agent may take, with read or write access set per system, and leave out everything else.

3

Write test cases

We collect real past examples with known correct outcomes, so we can measure the agent before it touches live data.

4

Add approvals and limits

We set which steps need a person to approve, how many steps it may take, and a spending cap on model usage.

5

Run alongside your team

The agent works in parallel with staff, and we compare results before giving it more responsibility.

What you get

  • An agent built for one defined task, connected to the tools it needs
  • Approval steps for actions that spend money or contact customers
  • A step-by-step log of every run
  • A test set you can rerun after any change
  • Usage caps and alerts on model spending

Guardrails on every agent we build

Permissions. An agent gets the least access that does the job. If it only needs to read invoices, it cannot edit them. Credentials stay on the server.

Human approval. Anything that spends money, sends a message to a customer, or changes a record that is hard to reverse waits for a person to approve it.

Logging. Every step is recorded: the request, each tool call, the result and the decision.

Failure handling. If a tool errors or the agent goes round in circles, it stops after a set number of attempts and hands the case to a named person with notes, rather than guessing. Agents that call several models or APIs rely on careful AI integration underneath.

Frequently asked questions

Can an agent run without anyone watching?

Some low-risk steps can, such as reading data and drafting. Anything that spends money, contacts customers or changes important records waits for approval. We widen unattended steps only after testing shows they are handled correctly.

What systems can an agent work with?

Anything with an API or a reliable export: CRMs such as HubSpot or Pipedrive, Google Sheets and Excel online, Xero, email and most booking or job management systems. Where a system has no API, we discuss whether a different approach would be safer.

How do you stop running charges getting out of hand?

Each agent has a cap on steps per task and a monthly usage ceiling with alerts before it is reached. We also use lighter models for simple steps and larger ones only where needed.

What happens when the agent gets something wrong?

Because approvals sit before any risky action, most mistakes are caught at the draft stage. The log shows where it went wrong, we add that case to the test set, and we change the instructions or tools so it is handled next time.

Should our first agent be a big one?

No. Start with one narrow job you can measure, prove it works, then add the next. Broad agents that try to do everything are harder to test, harder to trust and slower to get right.

Related services

Describe the task you would hand to an agent and we will send a fixed quote for building it, or call 0161 315 1151, or WhatsApp 07737 902425.

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