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Strategy & governance

Strategic Advisory & Governance

We assess where your data and systems stand, map what to build first, and put in the governance and training that keep the work paying off after we step back.

What does an AI and data strategy engagement include?

An engagement starts with a current-state assessment of your systems and data, then produces a reference architecture and a prioritized roadmap so you know what to build first. It also covers the governance and training that keep the work paying off after we step back.

  • Current-state assessments
  • Data and access mapping: where your data lives and who can reach it
  • Reference architecture: the blueprint for the platform you build
  • Evaluation strategy: how each model and agent will be measured on your data
  • Analytics centers of excellence that build capability inside your team
  • Virtual CIO services for organizations without dedicated technology leadership

What is a 90-day MVP scope?

A 90-day MVP scope is a prioritized first release sized to fit 90 days, with a build plan and an estimate. We reach it by starting with the decision you need to make and working backward to the data and the tools.

What does data and AI governance mean in practice?

Governance means clear rules for who can use which data and how every model and agent is held accountable, enforced by the platform rather than by habit. On one lakehouse we built, data governance moved from manual and inconsistent to automated and auditable.

  • Role-based access, so each person and each agent reaches only the data the job needs
  • Lineage and audit trails that show where data came from and who did what
  • Approvals that gate sensitive changes, with agents drafting sensitive actions for a person to approve
  • Evaluation: accuracy measured on your data before launch and monitored after
  • HIPAA controls for health data, as built for a health system

How do we move from AI experiments to something that runs across the company?

Replace isolated experiments with one platform that can run across the enterprise, with evaluation and governance built in from the start. One enterprise organization had AI experiments but nothing it could run across the business; the multi-agent platform we built tripled its assessment capacity while manual effort fell.

Will our team be able to run it after you step back?

Yes. Training, governance, and documentation are part of every build, so your team runs the system and knows why it works. For a hotel portfolio that grew more than 400% in a year, we built the pricing platform and helped establish and train the revenue management team that runs it.

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