For sales, recruiting, and GTM teams, SixtyFour is an AI agent platform that researches people and companies at scale, delivering intelligence through an API and MCP for building GTM workflows.
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 →
SixtyFour is working to become intelligence infrastructure for teams that need research agents inside products, workflows, and data pipelines. Its public positioning emphasizes people and entity research, including identity resolution and due-diligence work, alongside sales, recruiting, and GTM use cases. Its market presence is still early, with a quieter footprint than the larger data and enrichment platforms around it. The clearest current signal is its developer-facing posture: research intelligence delivered through an API and MCP for teams building their own agent workflows.
Octave
Knock
allGood
Aomni
OpenFunnelWhatnot, Airwallex, Turing, TRM Labs, Surge, Cloaked, Datacurve
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Business Profile
SixtyFour is an early-stage company, founded in January 2025 by Saarth Shah and Christopher Price and backed by Y Combinator through an initial pre-seed round. At roughly nine employees, it has moved quickly from founding to production use, with its people-and-company research agents already running at growth-stage technology companies including Whatnot, Airwallex, and TRM Labs. Public materials lean on benchmark comparisons against other AI research tools as the company's main proof point at this stage, with no funding beyond that initial round reported yet.
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
SixtyFour ships its research capability as an API from the outset — Intelligence, Search, and Workflows endpoints covering people and company research, identity resolution, and multi-step automated pipelines — with an MCP server that connects the same data directly into AI coding tools and agents. The product is built agent-facing rather than layered onto an existing dashboard, with API documentation structured for both AI-tool consumption and human developer use.
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