AI engineering, held to the standards of payments and security.
We build AI into real systems for organisations where mistakes are expensive. Every system ships with evaluation on your data, guardrails, human review and a full audit trail.
Five ways AI creates value in your business.
AI agents & workflow automation
Agents that take real actions in your systems, with permissions, approvals and full logs.
- Agents that call your APIs and tools with scoped permissions
- Approval steps before anything consequential happens
- Every action logged and replayable
- Fallback to a person when confidence is low
Search over your own knowledge
Assistants grounded in your documents and data, with sources shown for every answer.
- Retrieval over documents, wikis, tickets and databases
- Answers that cite their sources
- Access rules respected: people only see what they may see
- Quality measured against real questions from your team
AI features inside products
Classification, extraction, summaries and recommendations built into your software.
- Document and data extraction into structured fields
- Classification and routing
- Summaries and drafts for people to approve
- Recommendations with explanations
AI security & governance
Testing, red-teaming, access control and audit for AI in regulated settings.
- Prompt-injection and data-leak testing
- Permissions for agents and the tools they use
- Policy guardrails and content filtering
- Audit trails that satisfy compliance reviews
AI-assisted modernization
Understand and upgrade legacy systems faster, without losing their business rules.
- Mapping and documenting old code before changing it
- Test generation to protect existing behaviour
- Module-by-module migration plans
- Faster, safer upgrades of frameworks and platforms
How we make AI safe for production
The same discipline we apply to payments and security systems, applied to every AI feature we ship.
We measure accuracy on real examples from your business before and after every change.
Rules on what the AI may say and do, enforced in code, not just in prompts.
People approve anything consequential. The AI drafts; your team decides.
Inputs, outputs, sources and actions are recorded for review and compliance.
The right model for each task, caching and limits, so costs stay predictable.
Your data, your choice of model.
Regulated organisations often cannot send data to a public AI service. We design for where your data is allowed to go, from commercial model APIs to models running entirely on your own servers.
- Commercial model APIs
- Private cloud
- On-premise open models
- Inside your existing apps
Where AI earns its place in your business.
Examples of what we build, by industry. Every one runs with human review where decisions matter.
Decline and dispute analysis
An assistant that explains why payments fail and assembles evidence for disputes, for analysts to approve.
KYC and KYB document checks
Extract and cross-check identity and company documents, flagging gaps for review.
Transaction anomaly review
Surface unusual patterns with plain-language reasons, so analysts spend time where it matters.
Alert triage and enrichment
Rank SIEM alerts by likely severity and attach context before an analyst opens them.
Incident summaries
Turn logs and case notes into a clear timeline and a draft report.
Response playbooks
Automate containment steps, with approval gates for anything destructive.
Result review assistant
Check results against limits, history and method rules before sign-off.
Standards and SOP answers
Ask questions of ISO/IEC 17025, methods and SOPs and get answers with references.
Deviation and CAPA drafting
Draft deviation reports and corrective actions from the record, for a person to finalise.
Report drafting from field data
Produce programme reports from submitted data, with every figure traceable.
Policy document search
Find and compare clauses across large document collections.
Data quality checks
Spot missing, inconsistent or implausible partner submissions early.
Invoice and document processing
Capture, validate and route documents into your ERP or finance system.
Customer support agents
Answer routine requests and hand over to a person with full context.
Internal knowledge assistant
One place to ask about policies, products and procedures.
Legacy code understanding
Map and document old systems before changing them.
Test generation and review
Raise test coverage and review changes against your standards.
Migration planning
Plan framework and platform upgrades module by module.
From question to production.
- Pick one process where AI could save real time, and agree how success will be measured.
- Build a small working version on your real data, with an evaluation set from your team.
- Add guardrails, permissions, human review and logging before anyone relies on it.
- Launch to a small group, measure, then widen, with costs and quality tracked.
Have a process AI could take on?
Tell us about it. We will tell you honestly whether AI is the right tool, and what it would take.