AI built into the tools you already use

We connect a language model to your CRM, inbox, website or database so it does useful work inside the screens your team already opens.

AI IntegrationFixed quote after a free call, model usage billed to your own account
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AI Integration: where you are, the work, and where it gets you.

In plain English.

Most teams try AI by pasting text into a chat window and copying the answer back out. That works for one-off jobs, but it leaves the AI outside your systems, so nothing is saved, checked or repeatable. AI integration moves the model into the place where the work happens, such as a button in your CRM or a step in your order process.

We build these links using the official APIs from providers such as Anthropic (Claude), OpenAI (GPT) and Google (Gemini). The model receives only the fields it needs, returns structured data in a fixed format called JSON, and your system checks that data before saving it. Where a mistake would be costly, a person approves the result first.

Typical examples include drafting replies to enquiries from your CRM record, sorting incoming emails by type and urgency, summarising long job notes, or writing first-draft product copy from a spec sheet. We start with one task that clearly saves time, prove it, and only then look at the next.

It suits you if.

  • Your staff already use ChatGPT or Claude, but by copying and pasting
  • You have a CRM, helpdesk or database with an API you can connect to
  • One repeat writing or sorting task eats hours every week
  • You want AI output checked and logged, not trusted blindly
  • You need customer data handled in line with UK GDPR

What we do.

The right model for the task

We test two or three models on your real examples and pick on accuracy and running cost. Small, cheap models often handle sorting and extraction perfectly well.

Structured output, validated

The model returns data in a fixed schema, and your system rejects anything that does not fit. That stops a stray answer from writing nonsense into your records.

Human approval where it matters

Anything that reaches a customer or changes money can wait in a review queue. Staff approve, edit or reject with one click.

Your API account, your bill

Model usage runs on an account in your name, so you see the provider charges directly and keep access if you ever move on from us.

Logs you can read

Every request, response and cost is recorded, so you can see what the AI did, when, and what it cost per job.

How it runs.

  1. 01

    Free 15-minute call

    Tell Garreth which task wastes the most time. We check whether AI can do it reliably and whether your systems can be connected.

  2. 02

    Test on real data

    We run a sample of your own records through two or three models and show you the results side by side before quoting.

  3. 03

    Build and connect

    We wire the chosen model into your system, add validation and the review step, and test with your staff.

  4. 04

    Live and measured

    It goes live on one team first. After a few weeks we compare time saved and running cost, then decide on the next task together.

Questions people ask.

How much does AI integration cost?

We give a fixed quote after the free call and a short test on your data, so you know the build cost before committing. Model usage is billed by the provider to your own account, usually a small amount per request, and we set a monthly spend cap so there are no surprises.

Is my customer data used to train the AI?

The business APIs from Anthropic, OpenAI and Google do not train on your API data by default, and we check the current terms for whichever provider we use. We also send only the fields the task needs, so names and contact details often never leave your system.

What do you need from me?

Access to the system we are connecting (or an admin who can create API credentials), 20 to 50 real examples of the task, and someone on your team who can judge whether the AI output is good enough. A couple of short check-ins during testing is usually all.

What if the AI provider changes or retires a model?

Providers do retire models, often with a few months of notice. Because the prompts and schemas are kept separately from the code, switching model is a contained job. If you take an ongoing support plan, we watch for retirement notices and handle the switch for you.

Your next chapter starts with a conversation.

Nottingham & Derby / UK-wide

Let’s build
what’s next.

15 minutes with Garreth.
A real conversation about your business.

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