AI delivery
AI product owners and AI project directors to take your deployments through.
Compliance sets what a system has to prove. It still has to reach production. We place in your teams people who know how to run an AI project and who build regulatory requirements in from scoping, not the day before go-live.
The roles
Four ways to strengthen an AI project.
AI product owner
Carries the product vision, turns the business need into a backlog, arbitrates priorities and holds the line between business, data teams and compliance. Knows what a model can promise and what it cannot.
AI project director
Runs the project or programme end to end: milestones, risks, budget, vendors, committees and reporting to leadership. Carries the go-live decision and the evidence that justifies it.
AI programme PMO
Coordinates several AI projects in parallel: value-linked roadmap, progress tracking, risk register, change management and user adoption.
Scoping and prioritisation
A portfolio of use cases ranked by value and by feasibility, technical and regulatory, with a decision file per case, before budget is committed.
Engagement models
Fixed scope, or embedded.
Fixed scope
A scope, deliverables and a timeline agreed in advance. We carry responsibility for delivery and report on it to your steering committee.
Embedded
People placed inside your teams, under your direction, when the constraint is capacity rather than method. Vetted on real deliverables, mobilised in 7 to 14 days, with guaranteed replacement.
What changes
Compliance sits in the team, not at the end of the project.
Our product owners and project directors work with the same method as our auditors. The project moves forward with its evidence.
Deliverables
What the steering produces.
Next step
Describe your project.
Tell us the project, its stage and the role you are missing. We will come back with a profile or a scope.