SOLUTION · ENTERPRISE AI
AI in production, with the governance already attached.
Workflow automation, document intelligence and decision support, built the way a regulated buyer needs them: models versioned, the human decision points on record, and reasoning a reviewer can actually follow.
WHAT YOU GET
From use-case triage to governed production.
We start by throwing out the use cases that will never survive your risk review. Then we build the ones that will.
01
Use-case triage
Value, feasibility and risk weighed up before anyone writes a line of code.
02
Document intelligence
Pulling data out of contracts, claims and applications, sorting it, and checking it.
03
Workflow automation
Automation with a person in the loop, and obvious ways to escalate or override.
04
Decision support
Ranked recommendations that show their evidence, rather than an answer you have to take on faith.
05
Model governance
Versioning, evaluation sets, drift monitoring, and change control someone signed.
06
Integration
Deployed inside your existing systems, identity and data boundaries.
HOW IT WORKS
Explainability is a build requirement, not a report.
If you cannot trace a decision back to its evidence, it will not survive a fairness or audit review. So we build for that from the first sprint rather than retrofitting it when someone asks.
01
Triage
Every candidate use case scored on value, whether the data is ready, and how exposed it is to regulation.
02
Prototype
A narrow prototype on real data, with an evaluation set and a baseline to beat.
03
Govern
Versioning, human decision points, monitoring and a rollback plan — all settled before production.
04
Operate
Drift watched, re-evaluated on a schedule, changes controlled once it is live.
ENGAGEMENT MODELS
Start narrow, prove it, then widen.
MODEL 01
Use-case assessment
A short engagement that ranks and de-risks a backlog.
Value and risk scoring
Data readiness review
MODEL 02
Governed pilot
One use case to production with full governance.
Evaluation set and baseline
Monitoring and rollback plan
MODEL 03
Platform program
Shared AI platform and reusable components.
Reusable evaluation harness
Central model registry
ASSURANCE
What a risk reviewer receives.
These come out of delivery. They are not written up the week before an audit.
Model documentation
What it is for, what it learned from, what it is bad at, and every version it has been.
Human decision points
Where a person has to decide, and how that decision gets recorded.
Fairness review
Screening and scoring logic written down and open to review, with evidence behind each output.
Data boundaries
What leaves your environment, where it is processed, and how long we keep it.
Bring the use case your risk team keeps blocking.
We will tell you straight whether it can be governed, and what that would take.