AI assistants
Internal tools that answer questions from your own documents and systems, with a link to the source of every answer.
AI that knows your business, not just the internet
ChatGPT does not know your contracts, your products or your policies. We build AI applications that do — and we measure how accurate they are before you rely on them.
Measured Accuracy tested before launch, not guessed
Any model Claude, GPT, Gemini or open-source
UK hosting Available where your data requires it
Capabilities
What this covers
Document search
Ask a question in plain English and get the answer from thousands of files, not a list of search results.
Drafting and summarising
Generate first drafts of quotes, reports, emails and case notes in your own house style.
Data extraction
Pull structured fields out of unstructured text — contracts, CVs, tickets, transcripts.
AI agents
Multi-step tasks that use your tools to get work done, with approval checkpoints where the stakes are high.
Accuracy testing
A test set built from your real data, so every change is measured rather than hoped for.
Deliverables
What you get at the end
Built so your team can run and extend it without us. That is what a good handover looks like.
- Working application deployed to your environment
- Accuracy scores against a test set of your real data
- Source citations on every AI answer
- Cost per request monitoring and limits
- Handover so your team can maintain it
Typical technology
Chosen per project against what you already run and what your team knows — never out of habit.
- Claude
- OpenAI
- Gemini
- LangChain
- pgvector
- Python
- TypeScript
How we choose technology
Ways to start
How to get started
Start small. A fixed-price first step gives both sides real information before anyone commits a build budget.
Proof of Concept
One use case built against your real data, with an accuracy number at the end. No commitment beyond it.
Build
Full application with testing, safety checks and monitoring, deployed to your environment.
Ongoing
Models and prompts change. We keep testing, improving and controlling the cost.
Will our data be used to train AI models?
No. We use business API tiers where your data is contractually excluded from training. Where your rules are stricter, we can host an open-source model so nothing leaves your infrastructure.
How do you stop it making things up?
We ground answers in your documents and show the source for each one, so anyone can check it in seconds. We also test against a set of real questions with known answers before launch, and after every change.
Which AI model should we use?
It depends on the task, your budget and your data rules. We build so the model can be swapped without a rewrite, because this field moves fast and today’s best choice will not be next year’s.
Is our data good enough for this?
Often yes, for a narrower first use case than people expect. The proof of concept tells you honestly before you spend real money.
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Talk to us about llm development
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