Generative AI & LLM Applications
LLM-powered products grounded in your own knowledge.
Why this matters
Generic LLMs are impressive but ungrounded — they hallucinate, miss your context, and cannot see your data. Turning them into a trustworthy product means retrieval, evaluation, and careful engineering, not just a clever prompt.
Assistants, copilots, and RAG systems that draw on your data to generate accurate, useful answers — built for production, not just demos.
What we build
- Retrieval-augmented (RAG) assistants over your documents
- Domain copilots embedded in your existing apps
- Document summarisation and extraction pipelines
- Semantic search across knowledge bases
- Content generation with review and approval workflows
How we deliver this well
Ground the model
We connect the LLM to your data with retrieval so answers are accurate and cited.
Engineer for quality
We build prompts, chunking, and pipelines that hold up on real, messy inputs.
Evaluate rigorously
We measure accuracy, safety, and cost before anything reaches users.
Ship & monitor
We deploy with monitoring and feedback loops so quality improves over time.
What's included
A practical set of capabilities we bring to every engagement in this area.
Common questions
Related services
All servicesAgentic AI Development
AI agents that reason over your tools and data to complete multi-step tasks — with the guardrails, approvals, and observability enterprises need.
ExploreAI Platform & MLOps
MLOps foundations — training pipelines, model registries, deployment, and monitoring — so your AI keeps working reliably long after launch.
ExploreCustom Software Development
Purpose-built applications that fit your workflows, data, and rules instead of forcing your team into generic tools.
ExploreReady to explore generative ai?
Start with a discovery call. We'll understand your context and recommend the smallest step that proves value.