AI Application Development .
AI application development for UK products. LLM integrations, vector search, document intelligence and AI workflows that hold up in production.
What's included
Everything you get.
End-to-end AI feature development. From model selection to production monitoring.
LLM Integration
OpenAI, Anthropic Claude, Gemini, and open-source models (Mistral, Llama). Selected for your use case, cost profile, and data requirements.
RAG & Vector Search
Retrieval-Augmented Generation pipelines, embeddings, vector databases (pgvector, Pinecone, Weaviate). Your data, AI-ready.
Document Intelligence
PDF extraction, contract analysis, invoice parsing, summarisation. Structured outputs from unstructured documents.
AI Workflows & Agents
Multi-step AI agents, tool-calling, human-in-the-loop review flows. Built with Langchain or direct API orchestration.
Prompt Engineering & Evals
Systematic prompt design, regression test suites, and output evaluation. So AI quality doesn't degrade as your product evolves.
Production Observability
LLM cost tracking, latency monitoring, failure alerting, and usage dashboards. So AI is a feature, not a liability.
Why clients come to us
Problems we fix.
The problem
Your team built a GPT wrapper but it's unreliable in production
Our solution
We design proper prompt engineering, retrieval pipelines, and guardrails. So the AI behaves consistently at scale.
The problem
You want to add AI but don't know where it actually helps
Our solution
We run a scoping workshop to identify the highest-ROI AI touchpoints in your product. Then build those first.
The problem
Data privacy concerns are blocking AI adoption internally
Our solution
We architect solutions that keep sensitive data on your infrastructure. Local models, private endpoints, or data-residency-compliant cloud setups.
The problem
You've shipped an AI feature but have no real way to tell if it's actually helping
Our solution
We instrument proper evaluation. Accuracy tracking, user feedback loops, cost per outcome. So you know it's working, not just running.
How we work
A process you can follow.
Four stages. Each one has a clear output before the next starts.
- 01 Discovery
Understand the use case
We learn what the AI needs to actually do for your users, not just what's technically possible.
- 02 Design
Design the pipeline
Model selection, data flow and guardrails — planned before a single prompt is written.
- 03 Build
Build and train
We build, integrate and tune the AI feature, tested against real inputs, not demos.
- 04 Run
Monitor and improve
Usage, drift and cost tracked after launch, with iterations as real usage teaches us more.
Common questions
Quick answers.
Which AI model do you recommend?
It depends on your use case, latency requirements, and data-privacy constraints. We evaluate options and recommend the right fit. We're model-agnostic.
How do you handle sensitive data?
We design data flows that minimise exposure. On-premise models, private Azure OpenAI endpoints, or data sanitisation before any third-party API call. We discuss your compliance requirements before choosing an approach.
What does an AI project typically cost?
Scoped AI features start from £8k. Full AI-powered applications vary by complexity. We give a fixed-scope quote after a discovery session.
Can you add AI to our existing product?
Yes. That's most of what we do. We integrate into your existing architecture, data model and tech stack rather than requiring a rebuild.
Next step
Ready to start a AI Application Development project?
Tell us what you're trying to ship. We'll tell you honestly whether we're the right team for it.