Services
Each engagement is built around a specific problem, not a technology. Some of them end up using a large language model. Many use ordinary, well-tested software.
Services
RAG development and retrieval systems
Search and question-answering over your own documents that returns the right sources and shows where every answer came from.
What gets builtIntelligent document processing
Structured, validated data out of messy documents, with a known error rate and a person in the loop exactly where the system is unsure.
What gets builtLLM and AI integration
Language-model features inside your existing product or internal tools, connected to your data with permissions, tests and cost control.
What gets builtAI agent development
Agents that use tools to complete multi-step tasks, with narrow permissions, checks after every step and a full record of what they did.
What gets builtCustom software and internal tools
Software built around how your organisation actually works, from internal tools and APIs to data pipelines. AI only where it earns its place.
What gets builtPrivate and local AI
AI systems that keep your data on infrastructure you control, using open-weight models sized realistically for the job and the hardware.
What gets built
How an engagement works
Every project starts small and fixed in scope, so you see evidence before you commit to more.
Feasibility assessment
A short, fixed-scope look at your problem, your data and the options.
A written assessment and a clear recommendation, including "don't build this" when that is the honest answer.
Prototype
A working system on your real data, not a demo on someone else's.
The prototype plus an evaluation report with measured results.
Build
The production system, integrated with what you already run.
Tested, documented code that you own, with a proper handover.
Support
Monitoring, evaluation reruns and improvements as your data changes.
Agreed scope and response times, no lock-in.