For small and medium-sized businesses in the UK
AI implementation for businesses
In business, artificial intelligence does just two things: it brings in revenue and it saves money. We start with one task you can measure, build the solution around the way you work and run it on our own servers in UK or EU data centres.
One task to start
Something repetitive and measurable: the number of cases, the response time or the number of errors.
A measured result
A probation period on real data shows what the AI actually does before it takes on more.
Data under control
You know in advance where your documents, the index and the model sit, and what, if anything, goes to a cloud model.
What does AI implementation mean in practice?
AI implementation means putting artificial intelligence to work on real tasks in your business: choosing the task, connecting AI to your documents and tools, setting its limits and measuring the result. It is not buying a subscription and hoping the business fits around it.
What the AI revolution has brought is software made for one company. Instead of a subscription everybody shares, you get agents and small services built around your processes, and they grow with the business as it changes.
The trend is also moving towards European and independent software. That is exactly where we fit in.
What we implement
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AI agents
Programs that carry out a task from start to finish: replying to customers, reading invoices, preparing quotes.
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Agentic workflows
Whole processes built from several agents and the people who approve their work.
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Company AI on your own documents
Answers in plain English from your contracts, price lists and procedures, with the source shown for every answer. The method is called RAG.
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AI in your email
A language model on our own graphics card reads incoming messages and warns you about phishing. Nothing is deleted; a person decides.
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Memory: documents you can ask
You upload documents and ask questions in plain English, from inside ChatGPT too. Each company has its own separate index and files.
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Local AI on our own servers
Our own GPU servers let the AI run locally, so sensitive data does not have to leave the data centre.
Where your data sits: three levels
Company AI touches your data in three places: the search index, the model that turns text into numbers and the model that writes the answer. Where those three sit decides your level of privacy.
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Level 0: a public chat
You paste documents into a publicly available service. Convenient, but you do not control what happens to them.
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Level 1: knowledge with you, model in the cloud
Documents, index and search stay in a data centre you trust. Only the question and a few passages go to a large cloud model.
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Level 2: everything local
The model that writes the answer also runs on your provider’s own graphics cards. Nothing leaves the data centre.
For a price list and user manuals, level 1 is usually enough. For contracts, personal data, HR or medical records, choose level 2.
How we implement AI in a business
- Start with a question, not a purchaseWhat do you do by hand in the business, even though you do not have to? A three-minute questionnaire or a 20-minute call is enough to find out.
- Tidy up the documentsCurrent versions, one place, clear file names. AI is only as clever as the documents you give it.
- Choose one task with a measurable resultThe number of cases, the response time or the number of errors.
- Build it with limitsAccess only to the data and tools the task needs. A person approves the important steps, and everything is recorded.
- Probation, then the next taskWe measure the result on real data, improve it and move on. Each next task goes faster.
Why work with us
- Our own servers and GPU serversThe AI runs on our own hardware in UK or EU data centres.
- One company, one vaultEvery customer has a separate index and separate files. No other customer can look inside.
- A data processing agreementWe process your data under a written agreement.
- ISO 9001 and ISO/IEC 27001Our quality and information security management are certified. See the certificates.
- Open-source toolsLangChain and LangGraph, and open models such as Llama, Qwen and Mistral. You are not tied to one AI vendor.
- Email and AI from one providerWhen your email is with us too, your data does not travel between companies.
Questions about AI implementation
Where should a small business start with AI?
With one repetitive task you can measure. Replying to enquiries, reading invoices and preparing quotes are typical first tasks. Start with a question, not a purchase.
Do we need to train our own AI model?
No. You do not have to train a model from scratch or paste contracts into a public chat. It is enough to give AI proper access to your documents in a way that keeps them where they are. The method is called RAG.
Which AI models do you use?
That depends on how sensitive the data is: open models that run on our own graphics cards, such as Llama, Qwen and Mistral, or a large cloud model that receives only the question and a few passages. You know which in advance.
Will our documents be sent to a public AI service?
Not unless you choose that. The documents, the search index and the search itself stay in our data centre. With everything local, nothing leaves it.
How do you protect our data?
We process data under a data processing agreement, each company’s data sits in its own separate vault and our information security management is certified to ISO/IEC 27001.
From our blog
Plain-English pieces about AI agents, company AI and where to start.
Email is the only channel that works with everyone, belongs to the business and leaves a record. That is why it keeps growing – and why AI guards ours.
RAG lets AI answer from your company documents and cite its sources. We show how to build it so that your data never leaves the data centre.
An AI agent is not software out of a box but an employee who needs a proper induction. You fit the technology to the people, not the people to the technology.