Strategy

Decide what to build, in what order, and why.

A data and AI plan that finance can fund, engineers can build, and leadership can hold to account.

The problem

There are more data and AI ideas than budget. Roadmaps follow technology instead of business outcomes, pilots stall before production, and nobody can tie the plan to revenue, cost, or risk.

How we solve it

We start with the business decisions you want to improve and work back to the data, systems, and skills they need. You get a sequenced plan, a business case for each step, and a list of what to stop.

What we deliver

What you get.

The outcome

A funded plan where every initiative is tied to a business outcome.

  • Data and AI strategy and multi-year roadmap
  • Use-case identification, prioritization, and business cases
  • Target architecture and build, buy, or partner decisions
  • Operating model, roles, and ownership for data and AI
  • Briefings for executives and boards on AI readiness and risk
Accelerators

What we bring to this work.

Starting points we adapt to your data and systems. You keep what we adapt.

Data Readiness Assessment

Check whether your data can support a decision before you fund the work.

  • Profiling and lineage review of the sources in scope
  • A draft Decision Brief for the use case
  • A list of gaps, ranked by effort and by effect on the decision
  • A plan for the first build increment

AI Governance Starter

Policies, templates, and workflows to govern how your organization uses AI.

  • AI policy and acceptable-use standards
  • Risk assessment workflow and model and agent inventory
  • Evaluation Card and Control Register templates
  • Evidence packs for auditors, customers, and security questionnaires
How it starts

The first step.

We start with a working session with the leaders who own the decisions that matter most. We list the candidate uses of data and AI, check the data behind the most promising ones, and come back with a sequenced plan and a business case for the first step.

How we work
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