Generative AI consulting in the UK: LLM copilots, RAG pipeline development and agentic workflows, built on your data foundation with guardrails that actually hold.
The newest layer of the AI stack is interaction: applications that use large language models to understand requests, pull in relevant information and take action. As a generative AI consulting partner for UK and GCC businesses, we build copilots, assistants and agentic workflows, RAG pipeline development included, that sit on top of your data foundation and earn a real place in daily workflows, backed by the evaluation and guardrails needed to run safely in production.
LLM Copilots & Domain Assistants
We design and build assistants scoped to a specific job: answering customer queries against your knowledge base, drafting reports from operational data, summarising case histories for support teams, rather than yet another generic chatbot. Scoping tightly is what separates a tool people keep using from one that gets switched off after a week.
Retrieval-Augmented Generation (RAG)
We build RAG pipelines that ground LLM responses in your own documents, databases and knowledge bases, so answers reflect your actual policies, products and data, with citations back to the source, instead of leaning on the model's general training data. That's the gap between an assistant that's genuinely useful and one that's confidently wrong.
Agentic Workflows & Automation
Beyond answering questions, agentic systems can take multi-step action: triaging a request, pulling data from several systems, drafting a response and routing it for approval. We design these workflows with clear limits on what the agent can do on its own versus what needs a human in the loop, so automation speeds things up without quietly removing accountability.
Evaluation, Guardrails & Monitoring
Generative AI in production needs the same rigour as any other system, and then some. We build evaluation suites that test for accuracy, bias and failure modes before launch, guardrails that constrain what the model can say and do, and monitoring that flags drift and edge cases early, so problems get caught before a customer has to point them out.
- LLM copilots & domain-specific assistants
- Retrieval-augmented generation (RAG) pipelines
- Agentic workflows & multi-step automation
- Prompt engineering & fine-tuning
- Evaluation suites, guardrails & monitoring
The evaluation, guardrail and monitoring practices that separate production-ready AI assistants from demos.