Jobbrex provides a SaaS evaluation layer that validates AI-generated recommendations in procurement, logistics, planning, and production. The platform uses blind, bias‑controlled reviews by vetted supply‑chain experts to convert tacit judgment into quantitative scores, which are delivered via secure API integrations with ERP, WMS and BI tools. Real‑time reports and alerts enable enterprises to certify AI performance and intervene before operational errors occur.
Funding
Funding not disclosed
Founders
Product
Problem
AI models used in supply‑chain and manufacturing operations often lack a reliable mechanism for human‑expert validation, causing hidden bias, mis‑aligned recommendations, and costly operational errors that traditional performance metrics fail to capture.
Solution
Jobbrex delivers a dedicated evaluation layer that systematically validates AI outputs across procurement, logistics, planning, and production functions. The platform conducts blind operational reviews using bias‑controlled protocols, captures high‑signal expert preferences, and translates tacit judgment into structured scoring frameworks. These evaluations are automatically triggered and synchronized with existing ERP, WMS, and visibility systems via secure APIs, embedding validation results directly into operational workflows. Real‑time reports present quantitative scores, head‑to‑head comparisons, and deviation alerts, enabling organizations to certify AI performance and intervene before errors propagate. By surfacing operational signals that standard statistical metrics miss, Jobbrex ensures AI recommendations remain consistent with real‑world supply‑chain standards. The service is offered as a SaaS layer that can be accessed per evaluation or through tiered subscriptions.
Target Audience
Primary customers are enterprise supply‑chain and manufacturing organizations that deploy AI‑driven decision engines, as well as AI solution vendors seeking third‑party validation for their models.
Features
- Blind, structured reviews performed by vetted supply‑chain professionals using bias‑controlled protocols
- Expert preference modeling that captures high‑signal human judgments across procurement, logistics, manufacturing, and planning
- Operational scoring systems that convert tacit domain knowledge into reproducible, numeric metrics aligned with industry best practices
- Native integrations with ERP, WMS, visibility platforms, and process‑mining tools via RESTful APIs and FHIR‑compatible endpoints
- Automated execution engine that schedules evaluations, aggregates results, and pushes scores into existing dashboards or BI tools
- Secure, HIPAA‑grade data handling with end‑to‑end encryption, role‑based access controls, and audit logging
- Interactive web portal offering drill‑down reports, trend visualizations, and benchmark comparisons for AI model owners
- Research repository that publishes scoring frameworks, preference datasets, and operational benchmarks for continuous improvement