AI services
AI that works in production, not only in the demo.
We design, build and run AI features that are grounded in your data, measured against real cases and affordable to operate.
What we do
Eight AI services, one accountable team.
Take one service or combine them. Each is delivered by AI engineers working alongside our product, design and platform teams.
AI Strategy & Consulting
Find where AI pays for itself in your product, and what to leave alone.
Details
AI Agents & Automation
Agents that complete multi-step work across your tools, with approvals where it matters.
Details
LLM Evaluation & Guardrails
Test sets, automated evals and guardrails so quality is measured, not guessed.
Details
LLM Cost Optimisation
Model routing, caching and prompt work that cut spend without hurting answers.
Details
How we build
Four principles behind every AI system we ship.
- Grounded in your data
- Answers come from your content with sources shown, not from the model's general memory.
- Measured before launch
- A test set and automated evaluation tell you how good the system is, release by release.
- Safe by design
- Guardrails, permission checks and human approval sit where an error would be costly.
- Cost under control
- Model routing, caching and prompt design keep spend predictable as usage scales.
Engagement
How an AI engagement works.
Evidence first. You see results on your own data before committing to a full build.
- 01
Readiness review
We look at your data, your product and the task you want AI to handle, and tell you plainly whether it is a good fit and what it will take.
- 02
Proof on real data
A short, fixed-scope prototype on a sample of your own content, scored against a test set, so the decision to invest rests on evidence.
- 03
Production build
We build the feature into your product with retrieval, guardrails, human handover, monitoring and a cost budget designed in from the start.
- 04
Measure and improve
Every release runs against the evaluation suite. We track quality, latency and spend, and tune prompts, models and retrieval as usage grows.
Use cases
Where AI pays off, by industry.
Examples of work AI handles well today. We will tell you honestly if yours is not one of them.
SaaS and software
- In-product assistants that answer from your documentation
- Natural-language search and reporting
- Automated onboarding and support triage
Legal and compliance
- Contract review with cited clauses
- Policy and regulation question answering
- Document comparison and summarisation
Finance and fintech
- Document intake and data extraction
- Customer-service assistants with strict guardrails
- Internal knowledge assistants for operations teams
Sales and customer service
- Call transcription, scoring and follow-up
- Lead qualification agents
- Support chatbots with human handover
HR and recruitment
- CV screening support with human review
- Policy assistants for employees
- Interview scheduling and coordination agents
Real estate and property
- Listing and zoning research assistants
- Enquiry handling across channels
- Report generation from structured data
Find out if your product is ready for AI.
Tell us about your data and the task you have in mind. We will come back with a clear view of fit, effort and risk.