Services

From no AI to AI-native.

The engagement model — how Rose Point packages the work: a Sprint to find the leverage, a Build to deliver it, and Operate to keep it compounding. For the building blocks each engagement delivers, see Capabilities.

The engagement model

Choose the pressure point.

Every engagement starts with the Sprint. From there, the Build and Operate scale to fit the work, one module at a time.

01 Start here

AI Strategy Sprint

The entry point. A fixed-fee, one- to two-week diagnostic that maps your workflows, finds where AI creates real leverage, and hands back a prioritized roadmap with the first build scoped.

  • Fixed-fee, 1–2 weeks
  • Workflow and leverage map
  • Prioritized roadmap, first build scoped
  • Written go/no-go, fee credits toward Build on a mutual go
02 The core engagement

AI-Native Build

Your transformation from no AI to AI-native, delivered in named modules so you can see what you are getting. Context first, then one workflow live, then the next.

  • Context Layer
  • Custom apps and AI agents
  • Training and enablement
  • Acceptance tests built into every module
03 Keep it compounding

AI Operate

An ongoing partnership that maintains and expands the system after it goes live, including the acceptance tests that keep it honest. Where the moat actually forms.

  • Monitoring and maintenance
  • Acceptance test upkeep
  • Expansion to new workflows
  • Recurring partnership

Not ready to commit to a full Build? A standalone Build vs Buy assessment can run alongside the Sprint as a lighter second step.

How we deliver

The vision is full AI-native. The delivery is one function at a time.

Step 1 Context first

Encode the operator knowledge so everything downstream has something solid to stand on.

Step 2 One workflow live

Take one real function live end to end, with acceptance tests, before expanding further.

Step 3 Then the next

Add modules one at a time. Operate keeps the whole system maintained and compounding.

Good fit

Best for teams with real context and real constraints.

  • Leadership wants a credible AI plan before committing budget or engineering time.
  • Critical know-how lives in your people's heads, documents, and inboxes, not in systems.
  • Real workflows have repetitive research, synthesis, routing, or review work.
  • You need traceability, human accountability, and acceptance tests from day one.
Next step

Know the problem, but not the AI shape?

That is exactly what the Sprint is for. We will map where AI creates real leverage and scope the first build.