MERCOR
Tokenised Economic Right (not equity) to potential future liquidity from WLTH’s (Metamasters DAO Corp) allocation in Mercor. Slices are not securities of, nor endorsed by, the underlying company. They are unsecured contractual rights against WLTH (Metamasters DAO Corp). Residents of the U.S., UK, EU, and other restricted jurisdictions are ineligible. Review the full Terms & Conditions before purchasing.
Category: AI Infrastructure, Talent Marketplaces & Human-in-the-Loop Systems Stage: Late-stage private (Series C) Opportunity Type: Tokenised Economic Right
Company Overview
Mercor is a San Francisco–based artificial intelligence company operating at the intersection of talent marketplaces and human-in-the-loop AI infrastructure. Founded in 2023, the company initially launched as an AI-powered recruiting platform automating resume screening, interviewing, and candidate matching. Mercor has since evolved into a managed marketplace of domain experts—spanning engineering, science, law, medicine, finance, and journalism—used to train, validate, and refine AI models for enterprise and AI-lab customers. The platform combines automated matching with reinforcement learning workflows that integrate expert human feedback into model development. As of October 2025, Mercor raised a reported $350M Series C at a $10B valuation and remains privately held.
The Problem
Traditional hiring and talent matching are slow, costly, and ineffective for specialized, high-skill work. AI model training increasingly requires nuanced, domain-specific human judgment beyond generic labeled data. Generic data vendors struggle to supply consistent, expert-level feedback at scale. AI labs face fragmented expert sourcing and operational overhead when building human-in-the-loop systems. Scaling reliable expert participation across geographies and disciplines is operationally complex.
The Solution
An AI-powered marketplace that automates expert vetting, interviewing, matching, and engagement. Managed access to domain specialists who provide structured feedback for AI training and evaluation. Human-in-the-loop workflows integrated with reinforcement learning systems to improve model reasoning and judgment. A distributed workforce model enabling scalable expert participation across industries. Infrastructure that bridges talent sourcing with AI development pipelines.
Founding Team
Brendan Foody – Co-Founder & CEO; leads company vision and strategy. Adarsh Hiremath – Co-Founder & CTO; responsible for technology development and platform architecture. Surya Midha – Co-Founder & Board Chairman; provides strategic oversight. Sundeep Jain – President (since 2025); former Uber Chief Product Officer, overseeing product and operational scale.
Business Model
Managed marketplace model charging AI labs and enterprise customers finder’s fees, matching fees, and usage-based charges for expert contributions. Contractors engaged on hourly or project-based terms, with Mercor capturing a margin on facilitated work. Potential expansion into subscription or enterprise SaaS offerings tied to matching, orchestration, and reinforcement learning infrastructure.
Traction and Validation
Founded in 2023 with rapid progression through multiple funding rounds. 2024: Series A led by Benchmark at a reported $250M valuation. 2025: Series B raised $100M at a reported $2B valuation led by Felicis. October 2025: Series C raised $350M at a reported $10B valuation. Manages a network of 30,000+ domain experts across multiple professional fields. Reported average contractor earnings (~$85/hour), indicating marketplace liquidity and engagement. High-profile founder recognition and executive hires supporting scale and credibility.
Intellectual Property and Strategic Assets
Owned: Proprietary AI algorithms for expert vetting, interviewing, and talent matching. Owned: Reinforcement learning and human-feedback orchestration tools. Network Effects: Large, curated pool of domain experts enabling defensible human-in-the-loop infrastructure. Strategic Relationships: Engagements with leading AI labs and enterprise customers (specific counterparties not publicly disclosed). Data: Accumulated feedback, performance, and interaction data from expert-AI training workflows.
Disclaimer
No affiliation — nominative reference only.
The underlying company is entirely unaffiliated with this offering, with Metamasters DAO Corp, and with the associated Slices. Specifically:
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