Deal teams lose their edge when they rely on the same static, brokered lists as their competitors. GraphIQ.ai maps the entire B2B landscape into a living network topology of 300M+ organizations, their global hierarchies, and billions of operational signals. Sourcing teams use it to discover un-brokered lookalike targets; operating partners deploy it sitewide to accelerate portfolio GTM data infrastructure with zero seat-tax constraints.
Drop your top-performing portfolio companies in as anchor nodes. The graph analyzes structural commonalities — deep hiring signals, tech-stack infrastructure, and geographic footprint — to surface identical, un-brokered assets across 300M+ entities.
/platform/lookalike →Uncover true concentration risk and hidden market footprints. Trailing parent, subsidiary, and affiliate connections allows deal teams to map out a target company's complete corporate family tree prior to letter of intent (LOI).
/platform/identity-graph →Stop budgeting for data licenses every time a portfolio company scales its sales org. With an Entities Under Watch pricing model, operating partners can inject GraphIQ.ai data infrastructure into newly acquired assets with unlimited user seats.
/solutions/revops →Monitor high-conviction investment spaces via billions of operational signals. Track executive churn, sudden engineering hiring surges, or cloud infrastructure modernizations across thousands of target entities simultaneously.
/platform/signals →Traditional B2B data vendors restrict institutional research because they charge by individual user seats and utilize expiring monthly credit meters. GraphIQ.ai prices strictly by Entities Under Watch — monitor your entire investable universe year-round, allow every analyst and deal team member to query the system simultaneously, and leverage our native MCP server to run local AI reasoning models directly over the data layer.
Instead of querying static filters, you train our lookalike engine on an existing high-conviction asset. The graph evaluates interconnected data vectors to rank off-market targets based on structural similarity.
Yes. Via our native MCP server, your internal deal-sourcing algorithms, custom GPTs, or Claude Desktop clients can natively query, extract, and reason over our structured JSON-LD entity responses without writing bespoke API wrapper code.