Picture a common version of the problem: the founder has paid for an AI strategy session, has a long strategy deck, and still has someone copying call notes into HubSpot by hand every evening. Our AI consultant services exist for that gap. We sit down with your ops lead, pick one process, and build the agent that does it inside the systems you already run, with a fixed price and a success metric you can hold us to.
We are an AI consultant company whose consultants write the integration code themselves. One builder on r/AI_Agents who had shipped more than 25 agents found the ones clients kept paying for were simple: an email-to-CRM updater, an FAQ agent, a document parser. Answering a sceptic in the thread, the poster put it better than we could: "The value isn't the prompt it's the implementation, reliability, and ongoing ownership."
Advisory consultants, implementers and freelancers compared
Most people searching for an AI consultant in the UK are choosing between three kinds of help without realising it. The difference shows up months later, when the agent misfires on a Tuesday afternoon and someone has to own the fix.
| Advisory-only AI consultant | Implementer (us) | Freelancer or DIY | |
|---|---|---|---|
| What you get | Strategy, roadmap, AI policy | A working agent in your CRM, Teams or Xero | Whatever the brief says |
| Who builds it | You, or another supplier later | The same people who scoped it | One person |
| Pricing model | Typically a day rate or a fixed fee for the report | Fixed price after a free audit; optional £600/day retainer | Typically hourly, a day rate or a fixed fee |
| Risk we see | Nobody is left to build what the roadmap recommends | Scope too narrow at first (by design) | Code nobody else has reviewed reaching production |
A post on r/startups described a non-technical founder who got hacked before a bank deal after vibe-coding an entire MVP. One reply summed up the lesson: "vibe code a demo not a full product." If you are weighing a hire instead, our breakdown of the cost of hiring an AI developer versus an agency runs the in-house numbers, and buyers who already know they want a delivery shop can compare us as a UK AI automation agency.
How an engagement runs
An AI implementation consultant earns their fee in the boring middle of a project. Our sequence:
- Free 30-minute audit. You bring one process. We ask what system it starts in, where the data ends up and who checks it today.
- Written proposal within 48 hours. A fixed price, the integrations involved and a proposed success metric, for example, call notes on every deal record shortly after the call ends.
- Fixed-price custom build. We confirm the metric with you at kickoff. The first agent is live about 21 days after that.
- Metric check. Hit it, or we rebuild free or refund the build fee.
- Optional ongoing work. Some clients stop there. Others keep a fractional AI team on retainer to add agents and tune the ones they have. Average client tenure is 14 months.
What it costs
We charge in two ways.
- Custom project: fixed price excl. VAT, quoted after the free audit, in writing within 48 hours. We do not publish a range for custom builds. The scope sets the number, and you get one figure in writing.
- Fractional AI team: £600 per day (excl. VAT) for a team of 3-4 people. The typical retainer is 3 days a week, which is £1,800 a week or about £7,800 a month.
The full detail is on our pricing and engagement models page.
Works with your stack
An AI automation consultant who cannot name the field the agent writes to has not built one. Here is what we build on and what the integration does in practice.
- HubSpot. The agent can write call and meeting notes, plus extracted fields such as budget or timeline, to the contact or deal record. For Breeze Prospecting Agent, HubSpot lets you set enrollment triggers like form submissions or days since last engagement, and drafted emails show up in the sender's activity feed. In an r/hubspot thread about the Prospecting Agent, one commenter said enrollment criteria make or break these agents and suggested explicit do-not-enroll rules for recent unsubscribes, recent support tickets and existing opportunities. We write those rules in at the design stage. Our write-up on meeting transcripts written to the CRM shows the field mapping in detail.
- Salesforce. The agent can log activity and update opportunity fields, with a human sign-off on anything that changes a critical process. In an r/salesforce thread after Dreamforce '25, one commenter described the new Agent Builder as "an automated flow with explicit before and after actions and a prompt in the middle", which is roughly how we treat it.
- Pipedrive and Dynamics 365. The agent can create or update deals, activities and notes on the account or opportunity.
- Microsoft 365, Teams and SharePoint. The agent can live in Teams and answer from your SharePoint documents.
- Slack. The agent can post approvals and alerts to a channel so a person signs off before anything goes out.
- Xero. The agent can read invoices and bills for reconciliation and reporting. Our invoice OCR pipeline shows the extraction side of that work, with a person approving anything the model is unsure of.
- n8n, Make and Zapier. The glue: triggers, retries and routing between systems. We default to n8n or Make for ops work, and our LinkedIn AI SDR build started as Make.com workflows and moved to n8n.
Copilot Studio for Microsoft 365 shops
If your company lives in Teams and Microsoft 365, Copilot Studio is usually the right front end. Your staff already have Teams open all day. Microsoft positions it as a low-code studio where you can "build capable solutions without an extensive technical background", and for a simple FAQ agent that holds.
Past that point, one builder on r/copilotstudio reported a rougher ride. They made a timesheet and sign-in agent for a small M365 company and wrote up the experience: thin documentation, a UI that changed so often tutorials went stale, and weak generative answers out of the box. They moved the heavy processing to Azure Functions exposed as HTTP connectors, kept memory in Blob Storage and version-controlled the YAML in GitHub. Their verdict was that it is not ready for non-technical users, but the orchestration, role-based access and Teams integration made it worth persevering. That matches how we work: Copilot Studio in front, with Power Automate and Azure Functions behind it for heavy data processing, external APIs, memory and version control.
Cost modelling is part of the job
Microsoft updated its Copilot Studio billing page on 15 October 2026. Agents are billed in Copilot Credits per feature: a generative answer is 2 credits, an agent action 5, tenant graph grounding 10. Microsoft's own worked example puts one grounded, complex prompt at 12 credits, and custom agents are disabled when a tenant reaches 125% of its prepaid capacity. A commenter in another r/copilotstudio thread found the licensing confusing after the move to usage-based credits. So before we build, we estimate monthly credit use from the agent's design and expected traffic, because an agent that grounds every message in the tenant graph costs six times as much per answer as one that does not.
Why AI projects stall
The UK government's AI adoption research found about 1 in 6 businesses use at least one AI technology. The top barriers were "a lack of identified need for AI (71%) and limited AI skills, expertise and knowledge (60%)." The second is what an AI consultant for small business should fix. The first is not something we can fix by selling you a build.
There is a sceptical view worth reading too. Gartner, as reported by W.Media, predicts more than 40 percent of agentic AI projects could be cancelled by the end of 2027 "due to escalating costs, unclear business value or inadequate risk controls", and adds that many use cases positioned as agentic do not require agentic implementations. We agree with more of that than you might expect. A fixed scope, one success metric and a human approval step on risky actions are our answer to it. Sometimes the honest output of an audit is "use a Zapier rule".
Who this is not for
- You have not found a process worth automating. Book the audit if you like, but the likely answer is to wait.
- You want a strategy deck or an AI policy and no build. Plenty of advisory firms do that well.
- You run on M365 and need one FAQ agent in Teams. Try Copilot Studio's builder in-house first.
- You want agents running critical processes with nobody checking. We keep a person in the loop on critical processes.