WORLDTRACE

**WORLDTRACE — Find the Failure. Prove the Fix.** WORLDTRACE is an evidence-first AI-assisted operations platform designed to help supplier onboarding, procurement and IT operations teams investigate failures, make controlled decisions and verify outcomes. Business incidents often span disconnected systems: incomplete supplier records, failed API requests, conflicting data, documents and integration logs. Conventional monitoring can identify symptoms, while AI assistants may suggest remedies without proving whether changes are safe or successful. WORLDTRACE connects investigation to accountable action. The working prototype includes nine bounded specialist tools for PDF analysis, email inspection, network HAR analysis, ETL reconciliation, database checks, API contract testing, performance measurement, middleware validation and legacy record inspection. Six distinct operational responsibility stages coordinate research, security, execution, verification, action preparation and delivery. Meta Muse Spark Open-1026 provides real evidence-referenced advisory reasoning, generating hypotheses and recommended next steps from structured findings. Every model assessment is separate from authorization. WORLDTRACE demonstrates a complete approval-gated supplier correction in an isolated SQLite sandbox. The system detects a missing supplier record, requires explicit human approval, performs a limited correction and independently verifies the resulting database state. A separate adversarial demonstration proves that an unsafe correction is refused even after human approval when existing records conflict with the expected source. Recorded evidence includes hash-linked execution events and reviewable outcome artifacts. WORLDTRACE is an early-stage, open-source prototype using synthetic demonstrations. It does not claim production-system integrations, independent autonomous Meta agents or verified customer ROI. Our vision is to make AI-assisted operational resolutions safe, accountable and independently verifiable.