Make useful AI repeatable.

A connected approach

Connect evaluation, secure integration, operating cost and human accountability across an enterprise AI programme. We start with the actual operating process and connect the records, validation and people required to move the work forward. AI is used where it helps interpret information; business rules remain explicit.

AI security and agent-control programme

CISO: generative AI tools expose data through excessive permissions or unsafe actions.

Identity boundaries, approved tools, test attacks, logging and approval gates; AI assists triage; owners authorise consequential actions.

Pilot measures: Leakage tests, unauthorised-action attempts, blocked misuse and recovery behavior.

AI evaluation and unit-economics platform

AI programme owner: impressive demos have no quality or cost baseline.

Versioned evaluation sets, model/prompt comparisons, task-level costs and fallback monitoring; business owners set acceptance thresholds.

Pilot measures: Cost per successful task, unsupported answers, failure rate, latency and regression rate.

Agentic workflow orchestration

COO: an assistant can answer questions but cannot complete a controlled process.

Connect approved tools, define bounded actions, durable state, retries and audit trails; approvals govern consequential changes.

Pilot measures: Successful task completion, unauthorised actions, rollback success and exception burden.

AI model selection and evaluation service

Technology leader: teams cannot choose between models or explain quality differences.

Benchmark candidate models on permitted task-specific data, cost and latency; owners select the operating trade-off.

Pilot measures: Task success, cost, latency, language coverage and failure categories.

Managed AI platform and LLM operations

CTO: a successful AI pilot becomes expensive and unstable in production.

Version datasets/prompts/models, monitor drift and quality, route requests and maintain fallback; release owners approve changes.

Pilot measures: Regression rate, service availability, cost per accepted result and recovery time.

Enterprise AI integration and tool architecture

Enterprise architect: AI proofs of concept cannot connect safely to core applications.

Build authenticated tool interfaces, fine-grained permissions, event handling and observability; systems owners approve operations.

Pilot measures: Integration reliability, duplicate actions, permission violations and end-to-end traceability.

Start with a bounded pilot

Choose a business unit and a representative set of records. Measure today’s cycle time, errors and manual review. Validate unusual inputs, failed integrations and permission boundaries before expanding. Targets are agreed from that baseline rather than assumed from a generic savings percentage.

Common questions