Practice 01 · Applied AI
Systems that survive
contact with production.
Anyone can demo a model. The hard part is the system around it — the data contracts, the evaluation harness, the guardrails, the cost envelope and the audit trail. That is the part we build.
01 / Capabilities
What we build.
Five capability areas that compose into a single delivery. Most enterprise programmes start with one and pull in the rest within two quarters.
Agentic Architecture
Multi-agent systems designed around real business processes rather than demo scripts — with explicit tool permissions, deterministic fallbacks, human checkpoints and a blast radius you can describe on one page.
Data & Retrieval Platforms
The unglamorous foundation most programmes skip. Ingestion, entity resolution, chunking strategy, permission-aware retrieval and lineage — so the model answers from data the user is actually allowed to see.
Evaluation & Model Engineering
Quality you can measure before your customers do. We build task-specific evaluation sets, regression gates and cost/latency budgets, then tune, distil or fine-tune against them.
Decision Automation
Straight-through processing for regulated workflows — underwriting, claims, KYC/AML review, clinical intake, supplier onboarding — with explainability and reversal paths designed in from the start.
AI Platform & Operations
The internal platform that lets a hundred teams build safely: a paved road with shared gateways, guardrails, secrets handling, spend controls and telemetry, so governance is the default path rather than a review board.
02 / Engagement
Three ways in.
Fixed scope where it is honest to fix it, and a running team where the work genuinely cannot be specified up front.
Diagnostic
A senior pair maps your data, current AI estate, control gaps and regulatory exposure, then returns a prioritised build sequence with costed options.
- Current-state architecture map
- Use-case value and feasibility scoring
- Threat model and control gap analysis
- 18-month costed roadmap
Build
A cross-functional squad takes one high-value system from architecture to production, with evaluation, guardrails and runbooks delivered alongside the code.
- Production system, not a prototype
- Evaluation harness and regression gates
- Security review and red team pass
- Handover, runbooks and enablement
Embedded Team
A standing squad inside your delivery organisation, with an agreed capability transfer plan so your people take the wheel on a known date.
- Dedicated senior engineers and architects
- Platform and paved-road ownership
- Quarterly outcome reviews
- Structured capability transfer
03 / Principle
Security is an input,
not a review gate.
Every Applied AI engagement is threat-modelled by our own security practice before a line of production code is written.
That is not a policy we wrote to sound rigorous. It is the reason our systems clear enterprise security review in weeks rather than quarters. Identity, data boundaries, egress control, prompt-injection defence and audit logging are specified in the same architecture document as the retrieval strategy — because in an agentic system they are the same decision.
If you already have a security partner, we will work to their standards and hand them evidence in the format they use. If you would rather one team owned both sides, that is what we were built for.
Next step
Tell us what you are trying to build — or what you are trying to protect.
A 45-minute working session with the people who would actually run your engagement. No slideware, no discovery fee.