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AI 500 · AI

AI Integration Manchester

We connect OpenAI, Anthropic Claude and Google Gemini models to the software your business already runs, from CRMs and websites to internal admin tools. Our Manchester team builds the connection carefully, so API keys stay private, model outputs are checked and running costs stay visible.

  • 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

Putting a language model inside the tools you already use

Most businesses do not need a new AI product. They need one step in an existing system to do more, such as a CRM that drafts replies or a form that sorts enquiries. Integration means calling a model API at that step and handling what comes back.

The real work is choosing a model per task, since larger models are slower and dearer per request. It is keeping API keys on the server, never in browser code, and requesting structured outputs, such as JSON matching a schema, so your system gets reliable fields.

Models also fail: rate limits, timeouts and confident wrong answers. We build in validation, and a person reviews anything important. For multi-step workflows, see AI automation; this page covers wiring a model into your existing stack.

Teams that get the most from an API integration

It suits organisations happy with their current software who want one step inside it to do more.

  • Sales teams wanting enquiry summaries and suggested replies inside the CRM record.
  • Online retailers who want product attributes tagged for staff to approve.
  • Software companies adding an assistant feature to their own SaaS product.
  • Operations teams pulling details out of emails and forms, often alongside AI document processing.

How an integration project runs

1

Define the task and examples

We agree the exact step and gather 20 to 50 real examples with the answers you expect. These become the evaluation set.

2

Compare models on your data

The same examples run through candidate models from OpenAI, Anthropic and Google, compared on quality, speed and running cost.

3

Build the server-side layer

A service holds the keys, builds prompts, requests structured output and validates each response, behind an abstraction layer so the provider can change later.

4

Handle errors and limits

Retries cover rate limits and timeouts, and a fallback model or plain rule takes over if the first is down.

5

Launch and monitor

We release to a few users, watch accuracy and spend, then widen. The evaluation set is re-run after provider updates.

What you receive

  • A model comparison based on your own examples.
  • Server-side code with keys held in environment variables.
  • JSON schemas and validation rules for every response.
  • Retry, timeout and fallback handling with clear user messages.
  • Usage logging and spending alerts.
  • The evaluation set and a script to re-run it.
  • Handover notes on prompts, settings and switching provider.

Data terms and avoiding lock-in

Each provider publishes terms on how API data is handled and retained, and they change. We read the current versions with you before customer data is sent. Where personal data is involved, our AI policy and governance work covers the paperwork side.

Lock-in is the quieter risk. If provider-specific code is scattered through your application, moving to a better model means a rewrite. We keep every call behind one interface with versioned prompt files, so switching is a configuration change plus a test run.

Frequently asked questions

Which is better for us, OpenAI, Claude or Gemini?

It depends on the task, and the order shifts as new versions arrive. We test shortlisted models on your own examples and compare accuracy, speed and running cost. Often the answer is two models: a lighter one for routine steps and a stronger one for harder cases.

Will the provider use our data to train its models?

That depends on the provider’s current business terms and your account settings, which we review with you first. We also strip out personal details the task does not need, so less of your data leaves your systems at all.

Can you add AI to our existing CRM or website?

Usually, if the system offers an API, webhooks or plugins, as most modern CRMs and WordPress sites do. We check access in the first conversation so you know what is realistic.

How do you stop the model making things up?

Nobody can stop it entirely, so we design around it. Structured outputs, validation and grounding in your own data reduce errors, and customer-facing or financial outputs go to a person for approval. The evaluation set shows the error level before launch.

How are API running costs kept under control?

Model APIs bill by usage, so we log tokens per request, set spending alerts in the provider account and pick the lightest model that passes your tests. Our own work is a fixed quote agreed before we start.

Related services

Tell us the system and the task, and we will reply with a fixed quote. Request an integration quote, call 0161 315 1151 or message us on WhatsApp at 07737 902425.

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