Copilots and assistants
Chat and search tools that answer from your own policies, manuals and knowledge base, with sources shown.
AI and machine learning that works on your data
Practical AI for real workflows: assistants that answer from your documents, models that forecast and classify, and automation with a person in the loop.
Who it is forIs this
Is this
you?
- Teams buried in documents, emails or support tickets
- Operations that need forecasts rather than hindsight
- Leaders asked to "do something with AI" and wanting a sensible first step
- Companies that must keep sensitive data under control
What we deliver
What is included
Document intelligence
Extraction, classification and summarisation for invoices, contracts, forms and reports.
Forecasting and classification
Models for demand, churn, risk and quality, validated against your history before anyone relies on them.
Workflow automation with AI
Routing, triage and drafting steps inside your existing processes, with approval points for people.
Evaluation and guardrails
Test sets, accuracy checks and safeguards, so you can see how well it works and where it should not be trusted.
How it worksFrom first call
From first call
to running
Pick the use case
We choose one valuable, measurable problem and agree how success will be judged.
Prepare the data
We check what data exists, how clean it is and what must stay private, before any model is chosen.
Prototype and test
A working prototype is tested against real examples, and we report plainly where it falls short.
Deploy and monitor
We integrate it into your tools, add monitoring and review points, and keep tuning as data changes.
Building blocks
Typical building blocks
The exact stack depends on your systems, skills and budget. We recommend what fits, and explain why in plain language.
- Retrieval-augmented generation
- Document extraction
- Forecasting
- Classification
- Evaluation sets
- Human review
Common questions
Will our data be used to train public models?
We design so that your confidential data is not used to train public models. The exact setup, including where data is processed, is agreed in writing and depends on the platform chosen.
How do you stop an AI assistant making things up?
We ground answers in your own documents, show the sources, set the assistant to say when it does not know, and test it on real questions before launch. Human review stays in the loop where errors would be costly.
We have little data. Is AI still worth it?
Sometimes. Many useful assistants and document tools need documents, not large training sets. We tell you early if your data is not ready and what to fix first.
Let’s talk
Ready to talk about AI and machine learning?
Add it to your brief or write to us. A named lead replies within one working day with questions or a plan.
Innovate. Transform. Succeed.