Supplier Discovery

Supplier data aggregation and AI-driven matching reduce discovery time and improve sourcing decisions.

Business impact

• Supplier discovery time reduced by up to 75% — AI accelerates supplier identification, cutting time needed to find qualified suppliers
• Procurement operational efficiency improved — Streamlined supplier search and qualification reduce manual effort and delays
• Cost reduction through better supplier matches — AI helps find suppliers offering competitive pricing and quality, lowering costs

Data requirements

• Customs records and import/export data (Structured) — Used to build comprehensive supplier profiles and verify legitimacy
• Web scraping of supplier websites and directories (Text) — Collects up-to-date supplier information and capabilities for matching
• Supplier certifications and compliance documents (Structured) — Validate supplier qualifications and regulatory adherence

AI methods and techniques

• Predictive AI — Predicts supplier suitability and risk based on historical and real-time data
• Generative AI — Generates enriched supplier profiles and insights from unstructured data sources
• Symbolic AI — Applies rule-based logic to enforce compliance and qualification criteria

AI models and model families

GPT-4o, Claude, Neo4j Graph Algorithms, Custom ML models

Industries

Real-world evidence

2 documented case studies on record.

Companies using this: Home Depot, ScoutBee.