Startup profile · funding coverage
Cedar (Agentic Referrals) funding, valuation and investors
AI-native professional relationship network and employee-referral agents; Speedrun SR006, distinct from the medical-billing company Cedar.
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Funding, valuation & investors
Answer-first snapshotLatest funding
Not publicly disclosed
Latest known valuation
Not publicly disclosed
Total disclosed equity funding
Not publicly disclosed
Excludes debt, grants, acquisitions, secondaries, and IPO proceeds.
Current status
private
Stage not recorded · San Francisco, California, United States
Overview
Cedar, at getcedar.ai, builds an AI-native professional-referral network for growing companies. Its product talks with employees, maps their trusted professional relationships and surfaces candidates who may not apply to public job postings. Co-founders Greg Gunn and Beier Cai previously helped build Hootsuite.
The Speedrun SR006 official profile says the company booked roughly $2.5M in contracted revenue and elsewhere describes $3M closed during stealth. These are first-party disclosures with different measurement labels and update times; contracted amounts are not equivalent to cash collected or recurring revenue. Unlike job boards, Cedar's theory is to derive a durable relationship graph from employee referrals.
Employer-side metrics to investigate include referred-hire quality, graph coverage, privacy/consent, employee participation and whether data rights are clearly managed. **Identity note:** This is not the Cedar medical-billing company at cedar.com that VCT separately tracks.
Why Cedar (Agentic Referrals) is interesting
Cedar is a high-traction SR006 company based on its own reported $2.5M in contracted revenue, later updated to $3M in the portfolio narrative. Its identity is easily confused with the unrelated healthcare billing platform already covered by VCT.
Product & use cases
AI agent conversations mapping trust relationships and referral introductions for recruiting teams.
- Fast-growing companies identifying qualified employee referrals
- Recruiters improving candidate sourcing outside applications
- Talent teams managing consent and relationship-graph data
Competitive landscape
Edge: Private trusted-referral graph may become a recruiting moat if consented participation remains strong; source data accuracy and privacy are critical.
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LinkedIn incumbent
Professional profiles and recruiter search
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Gem adjacent
Recruiting CRM and sourcing workflows
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Manual employee referrals alternative
Human networks without systematic mapping
Notable stories
- Official Speedrun SR006 $2.5M contracted revenue statement: https://speedrun.a16z.com/companies/cedar
- Independent identity and product check: https://www.gpagent.ai/speedrun/company/cedar
- Separate VCT medical-billing Cedar: https://venturecapitaltracker.com/startup/cedar
Market / IPO context
Editorial / static context — not a live quote.
FAQs about Cedar (Agentic Referrals)
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Editorial note: AI tools assisted with research, structure, or drafting. Venture Capital Tracker retains human editorial responsibility for factual accuracy, relevance, and source quality before publication.