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AI Readiness Assessment

Know what to build, what to fix, and what to avoid.

A decision-grade AI readiness assessment for teams that need a clear view of use-case fit, architecture risk, data maturity, security constraints, and the first practical implementation path.

Is This Right For You

For executives and technical leaders deciding where AI belongs in the roadmap.

6 areas

Use case, data, architecture, evals, security, ownership

2 weeks

Typical diagnostic review window

Decision

Build, buy, kill, or sequence

  • A readiness scorecard across use case, data, architecture, security, evals, and ownership
  • A build, buy, kill, or sequence recommendation for priority opportunities
  • A practical roadmap that separates immediate wins from foundational work
Right for you when

When this is the right conversation

The organization has AI urgency but no defensible project sequence.

Teams disagree on whether the blocker is model quality, data quality, UX, or infrastructure.

Leadership needs enough confidence to fund the right next step.

Delivery Path

A practical path from decision to production.

1

Frame the decision

Clarify business goals, target workflows, stakeholder constraints, and what a good decision must answer.

2

Review the system

Assess architecture, data flow, integration points, security, eval needs, and delivery ownership.

3

Score readiness

Separate production blockers from manageable implementation risks and low-value distractions.

4

Plan the path

Deliver the recommendation, roadmap, risk register, and implementation scope options.

Capabilities

What we bring into the engagement

The work is principal-led and oriented around artifacts that make buying, building, and operating easier for technical and business stakeholders.

Readiness scorecard

A clear review artifact for leadership, product, engineering, security, and procurement.

Roadmap sequencing

Prioritize the work that unlocks production AI and defer work that does not affect the decision.

Use-case fit review

Determine where AI is the right tool, where deterministic automation is better, and where no build is the answer.

FAQ

Questions teams ask before getting started

Is this for technical teams or executives?

Both. The work produces technical detail, but the final recommendation is structured for funding, sequencing, and procurement decisions.

Can this be used before vendor selection?

Yes. It often prevents premature vendor commitments by clarifying architecture, data, and governance requirements first.