10 defined terms — identity graph, entity resolution, account hierarchy, buying group, and more. Plain-language definitions structured for both human readers and AI engine citation.
A structured network that resolves organizations, their employees, relationships, and signals into single canonical entities — rather than flat, disconnected rows of contact data.
Identity Graph →The process of mapping every name variant, subsidiary, and record — "Lucasfilm Inc," "Lucasfilm Ltd," "Lucas Film" — back to one verified entity ID, eliminating duplicates created by text matching.
The parent-subsidiary tree of a corporate family. Traversing it reveals hidden ownership, cross-sell paths, and the true parent behind a closed subsidiary.
The set of people involved in a single purchase decision — economic buyer, champion, technical evaluator, and end users — mapped across an account rather than treated as isolated leads.
Descriptive company attributes — industry, headcount band, revenue, geography. Useful as a filter, but static and shallow compared with a live graph signature.
A real-world event — job change, hiring surge, funding round, M&A, partnership — that indicates a buying window. GraphIQ processes billions of operational signals and links each to the right entity.
Signals →The full structure of an organization across legal entities, divisions, and international subsidiaries — the basis for prime-to-sub tracking and supply-chain dependency mapping.
Finding companies whose structural fingerprint matches your best customers — capabilities, growth signals, and graph position — instead of building an ICP from intuition or static filters.
Lookalike →An open standard that lets AI agents call data tools natively. GraphIQ hosts an HTTP MCP server so agents query the graph directly — reducing hallucination by grounding answers in verified structure.
MCP server →