Run Smarter · AI Agents

Custom AI agents for business that do the legwork, not just the typing

An AI agent doesn't just answer a question. It carries out a whole job: researching a new lead, drafting the reply, updating your CRM and booking the follow-up, then asks a person to approve anything that matters.

Take the AI Readiness Check See examples

Example

A new lead arrives by email or web form

The agent researches the company and the request

It drafts a reply and updates your CRM

Your team approves and the follow-up is booked

AI + Experts + Your Data

Any one of these on its own falls short. Together they give you the speed of AI with answers you can trust.

Does the heavy lifting

Plans the steps and does the legwork across your tools.

EXPERT

Checks it's right

Designs the guardrails and checks every action it takes.

YOUR DATA

Keeps it grounded

Your CRM, inbox and files, so it works with real information.

HOW IT WORKS

How it works, step by step

Here is a typical job, from the moment it arrives to the moment it is done. Watch it move through.

01A new lead arrives by email or web form
02The agent researches the company and the request
03It drafts a reply and updates your CRM
04Your team approves and the follow-up is booked

Where it pays off

Real examples of where AI Agents pays off. Filter by the part of the business you care about.

SALES

Lead research and first reply

Company details, needs and a tailored first reply, ready for approval in minutes.

All sectors

OPERATIONS

Supplier and price checks

Quotes compared across suppliers and summarised, with the best option flagged.

Trades and B2BEcommerce

ADMIN

Weekly report builder

Pulls figures from several systems, writes the summary and sends it every Monday.

All sectors

CUSTOMER SERVICE

Customer query resolver

Looks up the order, checks the policy and drafts the answer, escalating the tricky ones.

Ecommerce

ADMIN

Recruitment shortlist

Reads CVs against the role, books interviews and keeps candidates updated.

Professional services

SALES

Tender and bid helper

Reads the tender, pulls your past answers and drafts a first response.

Trades and B2BProfessional services

Start small. Prove it works. Then scale.

No big transformation projects. We find the one thing worth doing first, prove it with a pilot, then keep building month by month.

01 · 3 MINUTES

AI Readiness Check

Seven questions and a straight answer on whether AI fits your business yet.

02 · 1 DAY

1 Day Business Analysis

A day with your team to find the quickest wins. Free for a great fit.

03 · 2 TO 4 WEEKS

Pilot Build

One workflow built, tested and handed over, so you see it working first.

04 · MONTHLY

Monthly Support

Monitoring, training and the next build. Leave at the end of any month.

IN DEPTH

The detail, in 8 short parts

01 / 08

What Are AI Agents for Business?

An AI agent is software that uses artificial intelligence to plan and carry out a series of steps towards a goal. You give it a job, such as "research this new lead and draft a reply", and it works out what to do, uses the tools it has been given, checks the result and hands back finished work.

That's the big difference from AI assistants like ChatGPT, Claude or Copilot used on their own. An assistant answers the question you type. An agent goes further: it can gather context from your CRM, read an email, look up account details, write the draft and update the record, then ask a person to approve the parts that matter.

Most AI agents for business today run on large language models, the same kind of AI models behind the chat tools you may already use. The model handles the natural language processing: reading a messy email, understanding customer intent, writing a sensible reply. The agent design around it handles the rest: which tools it may use, which steps it must follow, and when it has to stop and ask.

You'll also hear the term agentic AI. It simply means AI systems that act, not just answer, and agentic systems like these need clear limits. Agentic AI systems are still new, so we keep every build practical, with a defined scope and a person in charge.

02 / 08

How AI Agents Work in a Small Business

Every agent we build follows the same simple loop. Understand the job, gather the relevant context, take the next step, check the result, then repeat until the work is done or a person needs to decide.

This is where the core idea comes in. AI on its own is fast but doesn't know your business. People on their own know the business but run out of hours. Your data on its own just sits there. Put AI, experienced people and your own data together and you get work that is quick, accurate and grounded in how you actually operate.

Tool use: how AI agents integrate with your systems

An agent is only useful if it can reach the places your work lives. Through tool use, AI agents integrate with your inbox, CRM, accounts package, order management systems, HR systems and shared drives. That can mean Microsoft 365, Google Workspace, Xero, QuickBooks, Shopify, HubSpot or other systems you already pay for.

Where a tool has a proper connection, we use it. Where it doesn't, we use workflow automation platforms such as Make, Zapier or n8n to bridge the gap. Agents can also reach external systems, such as supplier portals and booking tools, and older legacy systems can often be reached through exports, shared folders or email, so you rarely need to replace software to get started. Large firms connect agents to big enterprise systems; for an SME it's usually a handful of everyday apps.

Business context and memory

A good agent knows your business context: your prices, policies, tone of voice and the way you like things done. We give it a small knowledge base built from your own policy documents, templates and past work, so its answers reflect your business rather than the internet.

Where it helps, an agent can also remember past interactions and user preferences, for example how a regular customer likes to be contacted, so each reply builds on the last one.

Human in the loop by design

We design every agent with human oversight from day one. Low-risk steps, like reading an email or updating a note, can run on their own. High risk actions, like sending a quote, paying a supplier or changing account details, require human approval before anything happens.

In practice that means a person sees a short summary and a draft, then clicks approve, edit or reject. Some steps require human confirmation every time. Human confirmation keeps you in control, and every approval teaches us where the agent can be trusted with more.

03 / 08

Custom Agents vs Off-the-Shelf AI Tools

You can buy ready-made agents inside many products now. Microsoft Copilot Studio, Google's agent tools and features in CRMs and help desks all let you switch on an agent for common jobs. For simple, generic tasks they can be a good place to start, and we'll tell you if one fits.

Custom agents make sense when the job is specific to how you work. Traditional software follows fixed rules, so it breaks when an email is worded differently or a supplier sends a new format. A custom AI agent copes with that variation, follows your rules, connects to your mix of software systems and hands work back in the way your team expects.

Our approach to AI agent development is to use the tools you already have wherever possible, and only build what's missing. That keeps running costs down and avoids locking you into another platform.

Off-the-shelf agents: quick to switch on, good for generic tasks inside one product.
Custom agents: built around your specific workflows, data and approval rules.
A mix: often the best answer, with an off-the-shelf tool doing part of the job and a custom agent joining the dots.

04 / 08

Building AI Agents: How We Run Your First Agent

Building AI agents well is less about clever code and more about choosing the right job and testing it properly. Here's how a first agent usually comes together for an SME.

1. Pick one job with a defined scope

We start with the 1 Day Business Analysis to find one job worth automating: frequent, rule-based enough to check, and painful enough that saving the time matters. Good early candidates are lead research, supplier price checks, weekly reporting or first replies to customer queries.

2. Map the steps, data and approvals

We write down the user inputs, the systems involved, the decisions the agent may make and the points where it must ask. This becomes the agent's instructions and its guardrails.

3. Build, then test on real world scenarios

We build the agent and test it against real examples from your business, including the awkward edge cases: the angry email, the missing order number, the supplier who replies in a PDF. It doesn't go live until it handles them sensibly or knows to hand them to a person.

4. Go live with your team, then improve performance

Your team uses it on live work, with approvals switched on. We watch agent performance closely in the early stages, fix what trips it up and agree when it can take on more. A first agent is typically built and tested as a 2 to 4 week pilot, from £1,500.

05 / 08

Multi Agent Systems and Complex Workflows

Some complex tasks are too big for one agent, and multiple agents working together do them better. A multi agent system splits the work between separate agents, each with one clear role. One agent might read and sort incoming requests, another research the customer, and a third draft the reply, with other AI agents checking quality before a person approves.

Specialised agents with specialised tools are easier to test and improve than one agent trying to do everything. Multi agent frameworks help them pass work to other agents, and we keep a record of which version of each agent did what, so version management stays simple as you add more agents.

We don't start here. Most SMEs get the best return by proving one agent first, then adding more agents only where the next job clearly benefits. When you build agents one at a time, each can complete tasks reliably before you add the next. Many agents running complex workflows sounds impressive, but a single reliable one that saves real hours is worth more.

06 / 08

Costs, Time and Cost Savings

We keep pricing simple. A pilot to build and test your first agent starts from £1,500 and runs over 2 to 4 weeks. Monthly support, covering monitoring, fixes and the next build, starts from £750 a month and you can stop at the end of any month. Software and AI model usage costs depend on the tools chosen, and we'll show you an estimate of the monthly running costs before you commit.

Cost savings come from time given back to your team. Agents are good at the repetitive tasks people dislike: data entry, copying details between systems, chasing information and writing the same kind of reply again and again. When you automate tasks and automate workflows like these, people spend more time on decision making, customers and the work only they can do.

We agree how you'll measure it up front, usually hours saved per week, response times or jobs completed, and track it monthly so you can see whether the agent is earning its keep.

07 / 08

Risks, Data Safety and Human Oversight

AI agents can get things wrong, so we design for that. Clear limits on what each agent can touch, human intervention on anything risky, and logs of every action mean mistakes are caught early and are easy to trace.

Sensitive data needs particular care. We give agents the least access they need, keep personal data out of prompts where possible and follow UK GDPR principles. Data for our own tools is hosted in the UK, and we'll walk you through where any third-party AI service processes your information.

Human expertise stays at the centre. Agents prepare the work and solve problems within their brief. People make the calls that matter.

Least-access permissions for every agent and tool.
Approval steps for anything sent to a customer, supplier or bank.
A full log of what each agent did and why.
Regular reviews of agent performance, with changes agreed with you.

08 / 08

AI Agents UK: Who This Is For

We work with SMEs across the whole UK, from our base in Rainford, St Helens. Our AI agents suit businesses of 1 to 250 people who have a few busy processes, a mix of business processes spread across email, spreadsheets and software, and no in-house AI engineer to build and look after an agent.

If you're not sure whether an agent is the right answer, that's fine. Sometimes a simple automation or a well-set-up AI assistant does the job better, and we'll say so. The aim is the right tool for the job, not the most complicated one.

FAQ

Common questions

What is an AI agent?

Software that uses AI to plan and carry out several steps on its own, using your tools, rather than just answering one question.

Will it act without us?

Only where you allow it. Anything sent to a customer, supplier or bank is approved by a person first.

How long does it take to build one?

A first agent is usually built and tested as a 2 to 4 week pilot, from £1,500.

What can an AI agent do for my business?

It can take on multi-step jobs like researching leads, answering routine customer queries, comparing supplier quotes, building weekly reports and shortlisting CVs, with a person approving anything important.

Can I buy my own AI agent?

Yes. Many tools now include ready-made agents, and they suit generic tasks. A custom agent is worth it when the job depends on your own systems, rules and data.

How is an AI agent developed?

We agree one job and its scope, map the steps and approvals, connect the tools, then test it on real examples and edge cases before it goes live with your team.

What does a custom AI agent do?

It follows your own process from start to finish: reading the request, gathering context from your systems, doing the work and asking for approval where you've said it must.

Do we need technical staff to run an AI agent?

No. We build, test and monitor it, and train your team to approve and review its work. Monthly support covers fixes and improvements.