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AI Engineering & Custom AI Solutions

RAG pipelines, small language models and custom AI applications, engineered and integrated properly, not bolted on.

Checked 4 October 2026. Built from the full service page.

In short: RAG pipelines, small language models and custom AI built into your own data and applications. Starts with the task rather than the technology: who asks the question, what a good answer looks like, and what a wrong one would cost.

Who this is for

You want AI answering questions from your own documents, not the public internet
A one-size-fits-all API is too costly, too generic or too risky for your use case
You need AI built into a product or internal tool, with real governance and grounding

The problem

Bolting a raw language model onto your business without retrieval, grounding or evaluation produces confident, plausible, wrong answers, and no audit trail for why. In production, an ungrounded model is a liability, not a feature.

What we would do

Start with a discovery conversation about the task rather than the technology: who asks the question, what a good answer looks like, where the source material lives, and what a wrong answer would cost. Most failed AI projects are scoping failures rather than model failures.

  • If the questions people ask are already answered by a document nobody can find, the problem is search and governance rather than AI.
  • If the cost of a wrong answer is high and unbounded, design the human review step before the system, not after.

When we are not the answer: If you want a demonstration built quickly to show a board, plenty of people will do that faster and cheaper than us. We are worth paying for when the thing has to survive contact with real users and real data.

What is included

  • Retrieval-Augmented Generation (RAG) over your own documents and data
  • Small Language Model (SLM) selection, sizing and hosting
  • AI API integration and model configuration
  • Custom AI applications and internal tools
  • Prompt engineering and evaluation for reliability
  • Governance, cost control and monitoring for production AI

What the last 12 months looked like

The last 12 months
98%of tickets met SLA
<15 minaverage response time
Across Systech client engagements over the last 12 months, with 100% UK-based support.
Figures from our own service reporting.

What it costs

Scoped and quoted against your estate rather than sold from a rate card. We price what you already run, including the parts that are working and do not need replacing, and the quote itemises what is included so it can be compared line by line with anyone else’s. Managed IT support starts at £40 per user, per month if that is the wider question.

Three questions people ask

What is retrieval-augmented generation (RAG)?

RAG grounds an AI model's answers in your own documents and data.

Why use a small language model (SLM) instead of a big API?

Small language models can be cheaper, faster, more private and hostable on infrastructure you control. For many focused business tasks an SLM sized for the job outperforms a general-purpose API on cost and latency, without sending your data to a third party.

Can you integrate AI into our existing applications?

Yes. We build AI API integrations and custom applications that call models safely from the systems you already run, with the prompt engineering, evaluation and monitoring needed to keep them reliable in production.

Tell us what you need

A short call to talk through how your IT works today, what your team handles, and what you need from a provider. We will tell you plainly how we would approach it.

Book a call Or read the full service page

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