Machine Learning
Production machine learning for risk, fraud and forecasting — from feature engineering to MLOps and monitoring.
Artificial Intelligence
AI systems built for regulated, high-stakes environments
Design and deliver AI systems — document intelligence, LLM applications and decision support — that are secure and governed.
The problem
Why this matters
Many AI initiatives stall between prototype and production. The model works in a notebook, but integration, data access, security, evaluation and governance were never designed for — and in regulated industries those are the hard parts.
Common challenges
- Prototypes that never reach production
- Unclear evaluation of AI quality and failure modes
- Security and privacy risks of LLM integration
- Governance expectations for AI-assisted decisions
Our approach
How we work
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Choose the right problem
Prioritise use cases with measurable value and manageable risk.
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Design the system
Architect data, retrieval, model, guardrails and human oversight together.
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Evaluate rigorously
Build evaluation suites before and after deployment.
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Operate
Monitor quality, cost, drift and incidents in production.
Capabilities
What our artificial intelligence work covers
- 01
Document intelligence
Extraction, classification and validation of business documents.
- 02
LLM applications
Retrieval-augmented assistants with access control and citations.
- 03
AI agents
Tool-using agents with scoped permissions and human approval steps.
- 04
Decision support
Models that inform, rather than replace, expert judgement.
- 05
Evaluation engineering
Test sets, metrics and regression suites for AI behaviour.
- 06
AI governance
Model inventories, risk assessment and documentation.
Engagement
Deliverables and benefits
What you receive
- Use-case assessment and business case
- Production AI system
- Evaluation suite and quality baseline
- Governance documentation
What it changes
- AI that reaches production
- Measurable quality and known limitations
- Security and governance designed in
Standards & technology
FAQ
Frequently asked questions
Do you use our data to train shared models?
No. Client data is used only for the client’s own systems, under the agreed data-protection terms.
Discuss your artificial intelligence requirements
Let’s discuss it. Tell us what you are working on and an engineer — not a sales script — will respond.