AI Agent AI-Powered Menu Intelligence & Proposal Generation

Semantic Search

Uses vector embeddings (model: text-embedding-3-large, icon: search, color: #ec4899) to semantically match menu items to supplier product catalogs. Handles variations in naming, packaging sizes, and brands. Returns ranked matches with similarity scores, pricing, and availability from multiple suppliers. Utilizes tools: generate_embeddings, search_catalog, rank_matches, compare_suppliers.

View Core Logic Back to Worker

Semantic Search

Part of AI-Powered Menu Intelligence & Proposal Generation

Portal: Nexgile ProcureSense Nexus

Agent ID: catalog-matcher

Problem Statement

The challenge addressed

Manually matching menu ingredients to supplier catalogs with thousands of SKUs is time-consuming and error-prone.

Core Logic

How the agent solves it

Uses vector embeddings (model: text-embedding-3-large, icon: search, color: #ec4899) to semantically match menu items to supplier product catalogs. Handles variations in naming, packaging sizes, and b... Uses vector embeddings (model: text-embedding-3-large, icon: search, color: #ec4899) to semantically match menu items to supplier product catalogs. Handles variations in naming, packaging sizes, and brands. Returns ranked matches with similarity scores, pricing, and availability from multiple suppliers. Utilizes tools: generate_embeddings, search_catalog, rank_matches, compare_suppliers.

System Navigation

Explore related components

Portal

Nexgile ProcureSense Nexus

Digital Worker

AI-Powered Menu Intelligence & Proposal Generation

Current Agent

Semantic Search

Here