AI Strategy
AI Strategy from pilot to production.
Scope
We help leadership align on where AI actually changes margin, velocity, or risk—not slide decks that never ship. Engagements typically combine stakeholder interviews, workflow mapping, data readiness checks, and a clear decision record on build, buy, or partner.
How we work
- Prioritize use cases with explicit owners, data contracts, and measurable KPIs.
- Compare foundation models, fine-tuning, and RAG patterns against your latency, cost, and privacy constraints.
- Facilitate security, legal, and procurement reviews with concrete threat models and logging plans.
- Define pilot scope, evaluation sets, and kill criteria before engineering spends months building.
Deliverables
You leave with an executive-ready roadmap, RACI, budget bands, and a sequenced backlog your product and platform teams can execute without re-litigating strategy every sprint.
How it Works
- Use – case portfolio and dependency map tied to business outcomes
- Model and architecture options with cost, latency, and compliance tradeoffs
- Pilot charter with evaluation methodology and rollback triggers
- Security and governance checklist aligned to your regulators and insurers
Executive clarity
One narrative for the board and engineering on what ships first, why, and what proof is required.
Execution handoff
Backlog slices sized for delivery teams with acceptance tests and observability expectations baked in.
Qualifications & Requirements
- Sponsor and product owner available for weekly working sessions
- Read-only access to representative workflows and sample data policies
- Security or IT stakeholder for IAM, logging, and data residency constraints