For ABM and demand-gen teams targeting complex accounts, LeadGenius is a contact intelligence platform that pairs AI enrichment with human researchers to map buying committees, track role changes, and deliver opted-in, sales-ready contacts.
Presence & Market Position
Tracked · below panel floor — earned mentions are accruing toward the next scored window.
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
LeadGenius positions itself around live, on-demand contact sourcing rather than a static database, pairing AI-driven discovery with human verification to map buying committees and deliver opted-in, sales-ready contacts for account-based and enterprise demand-generation teams. Its published customer list includes some of the largest names in software and e-commerce, pointing to a positioning built around complex, high-value accounts rather than volume SMB outreach. Public conversation about the platform carries a quieter footprint so far, with visibility running mostly through its own site and customer case studies rather than third-party commentary.
Common Room
Vector
Crunchbase
UserGems
PocusGoogle, Microsoft, Amazon, Salesforce, Snowflake, eBay, DoorDash, Autodesk, Intercom, Square
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Business Profile
LeadGenius has operated in B2B data enrichment since 2011, building its model around pairing AI-driven sourcing with human researchers rather than relying on a purely static database. The company has raised $30.4M to date and runs independently, with a distributed team spanning more than 30 locations across 42 countries. Its published customer roster, which includes Google, Microsoft, Amazon, Salesforce, and Snowflake, points to a business built around enterprise and complex-account engagements rather than self-serve signups. Headcount and recent revenue figures aren't on the public record.
Agent Readiness
Not yet graded.
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
LeadGenius lists a dedicated API endpoint for its contact and enrichment data, though the current record doesn't show a public MCP, SDK, or agent-specific surface on file yet. The company's own AI use centers on its sourcing and tagging methodology, using AI and large language models to process contact and behavioral data at scale alongside human verification, rather than on exposing that data to external AI agents.
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