AI Readiness Assessment
A business diagnostic for deciding where AI can actually help, what risks need controls, and what kind of implementation support belongs in the first phase.
Business context
Current AI usage
Workflow pain
Budget range
Consent to review
What the full version will generate
Readiness score
A plain-English view of operational, data, budget, and risk readiness.
Use-case shortlist
The first workflows worth testing based on pain, value, and complexity.
Implementation path
A staged roadmap that separates quick wins from systems work.
Vendor fit
The kind of partner likely needed: consultant, automation shop, MSP, analytics, legal, or training.
Risk notes
Data, security, compliance, employee, and customer-facing considerations.
Current launch mode: submissions validate through a local API route and return a mock ID. Nothing is persisted yet. The next backend milestone is Supabase or Neon storage with review status, source notes, and follow-up workflow.
Tell us where the business is stuck.
The most useful AI projects start with a workflow, cost, delay, compliance exposure, or customer-service problem.