Retrieval-augmented generation over your own data
Help users find answers in approved documents, with references back to the source material.
AI systems for your business data and workflows
We build AI tools that work with your business data and existing systems. They can help your team find information, prepare documents and handle repeat customer questions — with quality and running costs measured from the start.
2015Building production software since
300Projects delivered
£2M+Processed by one platform
5.0Across 18 verified Clutch reviews
Technology chosen for the task
Selected to fit your product, existing systems and delivery requirements.
Python
Claude- LLM APIs
PostgreSQL
Supabase
Redis
Docker- REST APIs
Useful AI systems we build for businesses
We start with the task you want to improve and how you will measure success. A pilot tests answer quality, response time and cost against representative data before a wider rollout. Access controls, human review and fallbacks are planned around the consequences of an incorrect result.
Support deflection and AI help desks
Handle repeat questions and pass unresolved or sensitive requests to your support team.
Internal copilots and assistants
Give staff a way to search information and complete approved tasks across their existing tools.
Document and workflow automation
Extract, classify and prepare information for review, reducing repeated manual processing.
Semantic search and recommendations
Help customers and staff find relevant records or content when exact keyword matching is insufficient.
Evaluation and guardrail pipelines
Test representative examples, check permissions and define fallback behaviour before wider release.
An AI project in practice
The brief, the build and what changed for the business.
01
Social eventsFour years across the app and operations
Mobile app, backend, advertising tools, a digital marketplace and website.
4+ yrssupport across five codebases
02
Energy brokerageTenders, contracts and accounts brought together
Supplier tenders, contract management, brokerage accounting and client records.
100+suppliers per tender
03
Event technologyTicketing owned by the event team
Multi-organiser commerce, Stripe instalments and two native apps in one connected platform.
£2M+ticket sales processed
Test the value before you scale
You work with the same senior team from the first scoping conversation through to launch and support.
- 01
Model the economics
Token cost, latency and accuracy targets estimated per request before we build, so the feature is viable by design.
- 02
Retrieval and grounding
Your data chunked, embedded and retrieved so answers are grounded and traceable, not confidently wrong.
- 03
Evaluate and guard
An eval set, guardrails and fallbacks, so quality is measured rather than hoped for.
- 04
Ship and watch
Deployed with cost, latency and quality monitoring, and a routing layer to tune spend as you scale.
Answers, automation and a way to measure both.
We agree the scope with you before development starts.
Retrieval pipelines
Grounded RAG over your documents, with citations and a retrieval layer you can trust.
Support deflection
An assistant that resolves the repetitive tickets and hands the rest to a human cleanly.
Internal copilots
Assistants wired to your systems that save your team the search-and-copy busywork.
Token economics up front
A costed estimate per request, and model routing to keep it there at volume.
Evals and guardrails
A measurable quality bar, so “it feels better” becomes a number you can defend.
Production monitoring
Cost, latency, drift and quality are tracked continuously in production.
A closer look at what we do
Explore the technologies, integrations and specialist work behind each build.
Clutch★★★★★5.0 / 5.0Across 18 independently published client reviews
“They have a deeper technical knowledge than any web designer I've met to date.”
Frequently asked questions
01Which models do you use?+
We compare models against your quality, privacy, latency and cost requirements. We can use different models for different tasks and validate the choice on representative examples.
02How do you reduce incorrect AI answers?+
Retrieval from approved sources, citations, evaluation examples and human review reduce the risk. We also design fallback and escalation paths because no model can guarantee a correct answer every time.
03Can you put a real number on the running cost?+
Yes. Estimating cost per request up front is the first thing we do — before any build commitment.
04Do you work with our existing data and tools?+
Yes — we build retrieval over your documents and wire copilots into the systems your team already uses.
05How long to ship an AI feature?+
A grounded pilot in 3 to 6 weeks; a production, monitored system typically 8 to 12.
What could your team do with AI?
Bring us the workflow you want to improve. We will help define a useful pilot, the quality checks and the expected cost of running it.