AI solutions
AI that survives the move from demo to production
The gap in applied AI is no longer capability. It is the distance between a convincing prototype and a system that behaves predictably on data it has not seen, in front of people whose work depends on it. That distance is an engineering problem, and it is the one we solve.
What you get
Predictable behaviour, not impressive demos
Evaluation before deployment and monitoring after it, so quality is something you can observe over time rather than something you hope held.
Your data stays yours
Architectures chosen with data residency, retention and access in mind from the first design conversation — because retrofitting governance onto a live AI system is expensive and sometimes impossible.
A defensible cost model
Model choice, caching and retrieval design driven by what the workload actually costs at volume, not by what performs best in a one-off test.
What that involves
LLM applications
Assistants, extraction, classification and generation built into the systems people already use, rather than bolted alongside them as a separate tool nobody opens.
Retrieval-augmented generation
Grounding answers in your own corpus, with the retrieval quality work and the citation discipline that make the output trustworthy enough to act on.
Autonomous agents
Systems that carry out multi-step work against real tools, with explicit boundaries, human checkpoints and a record of what was done and why.
Computer vision
Detection, recognition and inspection pipelines for the cases where the information you need starts as an image rather than as a record.
MLOps
Versioning, evaluation, deployment and monitoring for models, so an AI capability is operated with the same rigour as the rest of your estate.
Technologies we work with
Models & APIs
- Anthropic Claude API
- OpenAI API
Retrieval
- RAG pipelines
- LangChain
- pgvector
- Pinecone
Systems
- Agentic workflows
- MLOps
Start with a conversation, not a specification
Tell us the problem and the constraints. If we are not the right fit we will say so. We reply within 24 hours on business days.