Incoming
support@yourco.uk
08:41Order 4812 — “can you confirm the delivery date?”
08:41Answer drafted from your own documents · 9s
08:42Routed to a person · awaiting approval
09:05Approved · sent · logged
LLM integration services
Language models, wired into the work. Not a chat box on the side.
Not a chatbot in the corner — capability built into the job itself. Our LLM integration services design, build and run language systems that read, write, extract and answer inside your real work, grounded in your own documents. Built around your work and deployed in your environment. Start with one job and grow from there.
Grounded
The send
A person approves it
The draft is ready in 9 seconds. Nothing goes out until someone says so.
01What it does
LLM integration services: what the model does here.
Pointed at one job and grounded in your material, language becomes real work. The jobs below are the shape, not the limits — you tell us the job; we build the system that does it.
02How we integrate it
From a public model to your reliable system.
- Step 01
We find the job worth handing over
The task that repeats fifty times a week, or the involved one that quietly takes whole afternoons. We start where the time goes.
- Step 02
We ground it in your data
The model works from your documents and context through retrieval, so answers are specific and verifiable — not generic.
- Step 03
We keep a person in the loop
For anything consequential, the system proposes and you approve. Judgement stays with you; the repetitive work does not.
- Step 04
We deploy in your environment
A private deployment we run and manage.
03Which model
The right model for the job — and where it runs.
We are not tied to one provider. We choose the model that fits the task and your privacy needs — and the choice decides where your data goes.
Frontier models
The strongest general models — such as Claude — for the hardest reading and writing. Fast to deploy on our own infrastructure, reachable through a secure login.
The specific text sent to the model does leave — under terms where it isn’t used for training and is only briefly retained.
Open models
A capable open model running on our own infrastructure, so no text is sent to a third-party model provider. A natural fit for sensitive or regulated work.
04Security & data
Enterprise LLM integration: private by default, not as an add-on.
01
Your infrastructureYour systems run on infrastructure we manage — never on shared servers, never on someone else’s platform.
02
Behind a secure loginAccess is over an encrypted connection, and the deployment is never listed or indexed.
03
Not used for trainingModel-provider terms forbid training on your data and retain it only briefly; the open-model option keeps every request on our own infrastructure.
04
A person approvesConsequential actions wait at a human approval gate. The system proposes; you decide.
05FAQ
What is LLM integration?
LLM integration is wiring a large language model into your existing systems and documents so it does real work — summarising, extracting, drafting and answering — grounded in your own data rather than the open internet. The model becomes part of the workflow: input goes in, a checked output comes back.
Language is one of three ways in under artificial intelligence. When the job is forecasting or scoring rather than reading and writing, that’s machine learning integration — and when the model should act on what it finds, that’s agentic AI. New to the idea? Read the plain-English guide to LLM integration.
What does LLM integration mean?
LLM integration is the work of connecting a large language model to your real tasks, tools and data, so it reliably reads, writes, extracts and answers within your business rather than sitting in a generic chat window. Done well, the model becomes a dependable part of a workflow, with a person approving anything consequential.
Which large language models do you use?
We pick the model that fits the job. For the hardest reading and writing we use strong frontier models such as Claude. Where data must not go to an outside provider, we run a capable open model on our own infrastructure. Either way the agent is built and tuned around your specific task.
Can an LLM work with my own documents and data?
Yes. We ground the model in your own files, knowledge and context using retrieval, so it answers from your material and can point to the source — rather than guessing from general training. This is what makes answers specific and verifiable instead of generic.
Is my data safe when an LLM is involved?
Agents run behind a secure login over an encrypted connection, and are never listed or indexed. With a model provider the specific text sent does leave, under terms where it isn’t used for training and is only briefly retained. With an open model running on our own infrastructure, no text is sent to a third-party model provider.
How is this different from just using ChatGPT?
A public chatbot is a blank box you prompt by hand each time. An integrated agent is tuned to one job, grounded in your data, wired into your workflow — so from your side it is one link, one button, one reliable result, with a person approving anything that matters.
Do I need to be technical to use it?
No. From your side it is a single web page: paste or upload, click one button, get a result. There is no editor, no server to manage and nothing to learn. We handle everything technical.
Start here
Tell us what you’d like an LLM to take off your plate.
Send a few details and we’ll set up a short call to scope it and give you a tailored quote. No obligation, no hard sell.