AI integration
Assistants, document processing, and automation built on language models — connected to your data and the tools your team already uses.
Where AI earns its place
- Assistants over your own knowledge — answers grounded in your documents, tickets, and product data, with sources.
- Document and data processing — extracting, classifying, and summarising invoices, contracts, emails, and support requests.
- Workflow automation — agents that carry out multi-step routine work and hand over to a person when they should.
- AI features inside your product — search, recommendations, drafting, and summarisation added to software you already run.
How I approach it
I begin with one process and a number to improve — hours saved, response time, error rate — and build the smallest thing that moves it. Every solution is measured against real examples from your business before it reaches users, and it comes with cost limits, logging, and a clear fallback for the cases the model gets wrong.
You are not locked in to one vendor: the model sits behind an interface and can be replaced as better or cheaper ones appear.
What you receive
A working integration in your environment, an evaluation set you can rerun, cost and quality monitoring, and documentation your team can maintain.