AI agents & copilots
Assistants that take real actions through tools, with guardrails and oversight.
Emerging Technologies
Gen AI
Generative AI that ships — agents, copilots, and RAG systems wired safely into your products and data.
- RAG grounded in your data
- Agents with safe tool use
- Model-agnostic (Claude, GPT, open models)
- Evals & guardrails
- Cost & latency controlled
Overview
Why it matters
Generative AI is easy to demo and hard to productionise. We build the part that's actually difficult: grounding models in your data with RAG, giving agents tools they can use safely, evaluating output quality, and controlling cost and latency — so what you ship is reliable, not just impressive once.
We're model-agnostic and pragmatic. We use the right model for the job (and the cheapest one that clears the bar), design for guardrails and human oversight, and keep your data private.
What we offer
Gen AI, end to end
RAG & knowledge systems
Answers grounded in your documents and data, with citations and freshness.
LLM app development
Production features built on LLMs — summarisation, extraction, generation, classification.
Prompt & eval pipelines
Systematic prompt engineering and evaluation so quality is measured, not guessed.
Model integration & ops
Caching, routing, fallback, and monitoring that keep AI features fast and affordable.
AI strategy & PoCs
Fast proofs-of-concept that prove (or disprove) value before you invest heavily.
How we work
Our approach
- 01
Frame
We pick a use case with real value and a clear way to measure whether the AI is good enough.
- 02
Prototype
A fast PoC grounded in your data to validate quality before building for production.
- 03
Harden
We add evals, guardrails, caching, and monitoring to make it reliable, safe, and affordable.
- 04
Ship & improve
We launch with human oversight and improve continuously as real usage reveals edge cases.
Questions, answered
Will our data be used to train someone’s model?
No. We use enterprise APIs and architectures that keep your data private and out of training sets, and we can deploy open models in your own environment when data residency demands it.
How do you stop the AI from hallucinating?
We ground responses in your actual data with RAG, add citations, constrain outputs, and run evaluation pipelines — plus human-in-the-loop where the stakes are high. You measure quality instead of hoping.
Which model do you use?
We're model-agnostic — Claude, GPT, and open models all have their place. We choose based on quality, cost, latency, and privacy for your specific task, and design so you can switch.
Ready to build your gen ai?
Tell us what you're building. We'll bring a senior team and a clear plan to ship it.
Start a project