Sound familiar?
- "Everyone says we should be doing something with AI. Nobody can tell us what."
- "We tried a chatbot, and it confidently told a customer something that wasn't true."
- "We hold thousands of documents and have no practical way to find anything in them."
What we deliver
- An honest assessment of where AI helps and where it is an expensive distraction
- Document processing — extraction, classification and summarisation of what you already hold
- Assistants grounded in your own content, answering with citations so a human can check them
- Automation of repetitive judgement work, with a person in the loop wherever the cost of being wrong is real
- Evaluation: measured accuracy on your own examples before anything goes near a customer
- Guardrails, logging and cost control, so behaviour stays predictable in production
AI is not magic
These tools write impressive things and sometimes make impressive mistakes. The difference between a useful system and an embarrassing one is the specification, the grounding and the evaluation built around the model — not the model itself.
We use them daily on real deliveries, which is exactly why we are cautious about where we point them.
Technology we build with
Claude & AI agents
Retrieval-augmented generation
.NET & C#
Azure
Power Platform
Evaluation & testing