A.1 · Artificial Intelligence & Machine Learning
Generative AI & Large Language Model Engineering
Retrieval, evaluation, and guardrails around a model you can defend
What we build
Production systems built on large language models, hosted or self-hosted. We build the retrieval layer over your own document estate with layout-aware parsing and hybrid search, prompt and context architecture that fits the task rather than the demo, evaluation suites that gate every change, guardrails that redact personal data before it reaches a model, and a model gateway that routes each call by cost, latency, and capability with automatic fallback.
Capabilities
- Retrieval-augmented generation over your own corpus, with answers bound to a citable source
- Permission-aware retrieval, so no reader is ever shown what they cannot open
- Evaluation suites and golden sets that block a prompt or model change if it regresses
- Personal data detected and redacted before it reaches a model, a log, or a trace
- A model gateway that routes by cost, latency, and capability, with caching and fallback
- Fine-tuning and distillation into smaller models you own and can run yourself
Related services
How it connects
Where it sits in the stack.
This service, and the two it hands off to. None of them can be optimised alone.
Generative AI & LLMs
Production systems built on large language models, hosted or self-hosted.
Agentic AI & Copilots
Multi-step agent runtimes wired into the systems an organisation actually runs on.
AI & Machine Learning · see serviceComputer Vision
Vision pipelines that run at the speed of the process they watch.
AI & Machine Learning · see serviceBring us the whole problem.
Tell us where the work is stuck, whether that is a model that never reached production, an application nobody can change, a data platform nobody trusts, or a plant the business cannot see. An engineer replies with a first read, not a sales deck.