04Rollout & Scale
Scale AI like a platform.
Own outcomes like a product team.
Rollout & Scale turns AI practice that works in one team into shared services, clear ownership and controls every team can build on. ARISE orchestrates the rollout inside your organization, against a roadmap we commit to.
- Forward deployed
- A roadmap with dates
- Vendor-neutral
- PricingPilot
- Search
- Checkout
- Onboarding
- Payments
- Support
Shared services
- Access
- Models
- Agents
- Policies
- Costs
- Provenance
Control plane
- Evaluation
- Traceability
- Governance
- Observability
Centralize what benefits from scale. Federate product delivery and product decisions.
Copy a working pilot into ten teams and you get ten versions of it: ten ways to reach a model, ten sets of rules, ten budgets nobody adds up. Scale works the other way round. What every team needs is built once. What makes each product different stays with the team that owns it.
The vehicle is a Center of Excellence (CoE): a small team, usually grown out of the pilot team, that builds what every team needs once and hands delivery to the teams as they become ready. That is how a pilot becomes your operating model.
A CoE is a lever on the whole organization's AI maturity. It gains reach by having to own less: maturity comes from proven practice, not from decree.
- L1Personal chat AI
- L2Personal agents
- L3Team product loop
- L4AI operating model
- 01
Scale what's proven
Only practices and capabilities justified by a real pilot are rolled out. Everything else stays an experiment until it has earned its place.
- 02
Build once, share as a service
What every team needs, from model access to evaluation to cost control, becomes a shared service instead of being rebuilt team by team.
- 03
Every service has an owner
Ownership becomes explicit: who runs a service, who approves changes to it, and who answers when something goes wrong.
- 04
Control grows with adoption
Evaluation, traceability, governance and observability expand with every team that comes on board, so risk never grows faster than use.
- 05
Teams keep their outcomes
Teams gain leverage without giving up accountability for their own product outcomes. Product decisions stay where the product is.
The team that proved it builds it for everyone.
The people who made the pilot work know what holds and what was luck. They form the core of a Center of Excellence, joined by people from the teams that come next. The first months go into agreeing what becomes standard. That takes some friction, and the standards come out of it.
Start from the pilot
The CoE forms around work that already runs. It hardens the pilot, writes down what worked, and turns it into the first shared services.
Hand delivery to the teams
As teams become ready, delivery moves to them. The CoE keeps what every team uses: platform, security baseline, evaluation, cost control and enablement.
Pass capability on, don't collect work
Two models fail: a centre that sets rules without shipping anything, and a centre every AI initiative has to queue for. A strong CoE does neither.
Pre-CoE
Today- AI efforts remain fragmented
- No shared operating model
- Knowledge, standards and delivery stay local
Forming
2–12 months- The CoE forms around real work
- A lighthouse use case creates the starting point
- Governance, platform and delivery are proven together
Scaling
1–3 years- Proof becomes a system
- Standards, enablement and shared capabilities consolidate
- Delivery federates into product teams
- The model becomes repeatable
Maturing
Ongoing- The operating model belongs to the organization
- The CoE sets guardrails and advances the practice
- Teams deliver federated within one shared system
CoE maturity
Forming takes months, scaling takes years. The roadmap says which capability is ready when.The CoE in the maturity model
Inside your organization, against a roadmap we commit to.
Scaling is orchestration work: teams, platform, security and budget have to move in step. We take that on, in person and on dates, and hand it over once it runs.
One delivery team
Product direction from ARISE, engineering from partners we have vetted, working as one team inside your organization.
Hover over the team to see who does what.Tap a person to see who does what.
- 01
Harden
What ran under close supervision gets tests, monitoring and named owners.
- 02
Commit
A roadmap with dates: which capability is ready when, for which teams. Only what the pilot justified goes on it.
- 03
Build
The shared services below, built in the Center of Excellence with your people.
- 04
Hand over
Team by team, delivery moves to you. Our role shrinks as yours grows, and our exit is on the roadmap from day one.
What gets built: one control plane for AI in your organization
One layer every team builds on, instead of each team building its own. It grows with adoption: every team that comes on board adds to evaluation, traceability and observability, not to the risk.
One team, and a record of what it does.
The pilot team gets one way in to models, tools and company context, and every run is logged. That is all it takes to run one team safely.
- Access
Access for every team
Models, tools and company context through one entry point. No team negotiates its own accounts and keys.
Platform access · AI gateway
- Evidence
Results you can trace
Every run is logged: input, output, decision, approval. Any result can be traced back to how it came about.
Provenance · Audit trail
Where appropriate, we deliver platform and security baselines. Binding legal assessment remains outside our scope.
AI makes each team faster. The control plane means the next team starts where the last one stopped, and nobody pays for the same groundwork twice.
Before you scale.
What we agree with you up front
What the engagement settles
Binding legal assessment remains outside ARISE's scope.
Bring your pilot and the teams that want it next.
We look at what the pilot proved, what the next teams need, and sketch the first roadmap with you.
Discuss rollout & scaleNo pilot yet? Start with the assessment