Custom Generative AI Development UK

Custom generative AI is a solution built around your data, workflows, and security requirements, rather than a generic chatbot. It connects large language models to your own systems using techniques such as retrieval-augmented generation (RAG), tool-calling, and AI agents.

We build custom generative AI on Azure OpenAI and Semantic Kernel, so the model reasons over your enterprise knowledge while your data stays inside your security boundary.

Yes. We build document assistants on Azure OpenAI and Azure AI Search that answer questions across large libraries of manuals, specifications, reports, and procedures, citing the source section for every answer. Accuracy comes mainly from structure-aware chunking, hybrid keyword and vector search, and an evaluation set agreed with your experts.

Governance is designed in from the start. Each model call is recorded with the user, the action, the model used, and its token counts, so you can report cost per user and per action. Our guides to RAG accuracy for technical documents and AI usage governance and token tracking on Azure explain both in detail.

Off-the-shelf AI tools (like standard Copilot or ChatGPT) work with general knowledge. Custom solutions connect AI to your data, processes, and systems, giving you context-aware, accurate outputs that generic tools can't produce. They're also built to your security and compliance requirements.

We build on Azure OpenAI Service, which means your data never leaves your Azure tenancy and is never used to train public models. We enforce role-based access controls, apply encryption in transit and at rest, and conduct security reviews as part of every delivery.

Not necessarily. The AI Opportunity Assessment helps us understand the current state of your data and what's needed to make each use case viable. We can help you identify gaps and pragmatic approaches to address them as part of the project.

Our model-agnostic architecture is designed precisely for this. We abstract the model layer so that swapping to a new or better model is a configuration change, not a rebuild. Your business logic, data pipelines, and integrations remain intact.

Yes. We're experienced in extending and customising Microsoft Copilot using Microsoft 365 Copilot extensibility features, Copilot Studio, and Azure OpenAI, so we can build on top of licences you already have and maximise your existing investment.

Yes. We are a UK-based consultancy providing bespoke AI development for organisations across the United Kingdom. Engagements are scoped through an AI Opportunity Assessment, built on Azure OpenAI so your data stays within your security boundary, and handed over with full source code ownership. Book a consultation to discuss your use case.

Multi-agent orchestration uses several specialised AI agents that work together to complete complex tasks. Instead of one general-purpose agent doing everything, each agent has a focused role: one might retrieve data, another might analyse it, and a third might take action or generate a report. The agents coordinate through a defined workflow with tool-calling and safety controls. We build these on Semantic Kernel and Azure OpenAI with full observability and human-in-the-loop approval where needed.

Yes. Our AI Copilot Accelerator is listed on G-Cloud 15. It grounds Microsoft 365 Copilot in your internal knowledge using retrieval-augmented generation (RAG) over SharePoint, Teams, and other sources, with configuration, retrieval setup, and governance included. Bespoke generative AI development can also be procured through Digital Outcomes and Specialists 7 (DOS 7); see our Government Commercial Agency supplier page.