graphify

Build a knowledge graph from product catalogs and customer conversations by extracting entities and relationships, then clustering and scoring them to reveal cross-sell opportunities. Graphify processes these B2B sources to generate a queryable map of product relationships and customer buying patterns.

Sales intelligence knowledge graph querying is the process of mapping product relationships, customer behaviors, and market trends to uncover hidden cross-sell paths. It connects scattered B2B data from CRM records and research notes into a structured graph for runtime exploration.

Yes, you can use CRM records and ChromaDB data to map customer buying patterns. Graphify extracts companies, people, and deals from these sources to cluster behavior and identify referral bridges within a customer intelligence graph.

Connect competitors, markets, and regulations by building a market research graph that links these entities to prioritize lead-discovery focus areas. This approach helps craft differentiated strategies by revealing competitive insights and regional trends.

Yes, you should organize input data such as product catalogs or research notes in a designated folder like product-kb/ before extraction. Graphify requires structured B2B sources to build the graph and output results into graphify-out/ for querying.

The best way to find cross-sell opportunities is to convert scattered business information into a connected knowledge graph. By mapping shared product attributes and customer relationships, you can uncover hidden cross-sell paths that are difficult to spot manually.