The data infrastructure layer RevOps leaders deploy under AI-native GTM.
RevOps leaders are building AI into GTM workflows faster than their legacy data infrastructure can support it. The models are ready and the agents are deployed, but the answers come back wrong because the underlying data layer is a messy CRM, a contact database with a quarterly refresh cadence, and a signal feed that doesn't understand corporate hierarchy. GraphIQ.ai fixes the foundation. We resolve 287M organizations into structured context.
Architectural capabilities built for RevOps infrastructure.
CRM Enrichment & Deduplication Control
/use-cases/crm-enrichment →Territory Design & Graph Scoring
/use-cases/territory-planning →Account Hierarchy Management
/use-cases/account-expansion →AI-Ready Grounding Layer
Grounding model answers in resolved entities instead of scraped text.
/use-cases/ai-agent-data-layer →Pricing that scales the way your team actually grows.
Legacy B2B data providers charge per seat. GraphIQ.ai bills on Entities Under Watch instead — add as many team members as you need, connect multiple engineering codebases, and run as many AI agents as the work requires.
Frequently asked questions
How does GraphIQ.ai alter standard data warehousing syncs?
Every sync delivers structured JSON-LD entity responses instead of flat rows.
Can we feed signal arrays into custom ML models?
Yes, via API and MCP.
Does GraphIQ.ai replace our CRM?
No — acts as foundation layer underneath Salesforce or HubSpot.