// preliminary ai-readiness map
AI Can’t Use Data It Can’t Reach
Pick one operational question you wish AI could answer. We'll generate a preliminary AI Data Access Blueprint showing where the initiative is likely to stall: data access, legacy systems, governance, or ownership.
$5,000 audit fee credited back if you hire The Mad Botter for the implementation.
~/operations - ai-data-access
> ask_ai("which jobs are at risk of shipping late?")
x ERROR: source of record = legacy_erp.dbf
x no API. no schema. no access layer. no audit trail.
> generate_blueprint --preliminary
+ likely systems mapped
+ access blockers identified
+ governance boundary flagged
+ next step scoped
Most AI pilots do not fail because the model is bad. They fail because the useful answers live in systems that were never designed to be queried by an AI agent. The paid audit validates the access path, and the $5,000 fee is credited back if you move forward with The Mad Botter for implementation.
// generate blueprint
Map the access problem before buying another AI tool.
// what this leads to
The $5k audit validates the map, then credits back into implementation.
The AI-Ready Data Audit turns a self-reported blueprint into a one-week engineering plan: Data Exposure Map, MCP Server Spec, Governance & Access Model, and Build Estimate & Roadmap. If you hire The Mad Botter for the implementation, the $5,000 audit fee is credited back toward the build.