We build LLM applications and AI agents grounded in your own documents and systems. That means retrieval-augmented assistants with citations, document and email processing, and tool-using agents with guardrails, permissions and human checkpoints, all measured against a test set so accuracy is proven rather than assumed.
Ask it anything in your documents.
An illustration of a knowledge assistant: it answers from your own files and shows the sources, so people can check.
Pick a question to see how the assistant answers from your documents.
Built to hold up.
Knowledge assistants
Retrieval-augmented chat over your documents, tickets and wiki, with source citations you can check.
Document and email processing
Extract, classify and summarise incoming documents and messages, then feed the result into your systems.
Agents with guardrails
Tool-using agents that take real actions, with permission boundaries, logging and a human checkpoint for risky steps.
Evaluation and cost control
Test sets, quality metrics and model choices that keep accuracy high and the bill predictable.
Questions we often get.
Whichever fits the job and your privacy needs: hosted models from the major providers, or open-source models running in your own environment when data cannot leave it.
Have something that should run itself?
Tell us what is slowing your team down. We will come back within one working day with an honest view on whether it is worth building and what it would take.