AI Data Startup Mercor Raises $750M Funding at $20B Valuation to Train and Test Enterprise AI Agents

Mercor, the San Francisco-based AI data and evaluation company, has raised $750 million in Series D funding at a $20 billion valuation—double its valuation from just over a year ago. The round includes participation from Benchmark, Felicis, General Catalyst, NVIDIA, Salesforce, Sapphire Ventures, Apollo, G Squared, Glade Brook Capital, StepStone Group, XTX Ventures, Zoom, and Fundomo .

The funding follows Mercor’s $350 million Series C at a $10 billion valuation in October 2025. The company reported an annualized revenue run rate above $2 billion in July 2026, though Tech Funding News noted this is gross billings, with contractors keeping roughly 60-70%, putting net revenue at an estimated **$600 million to $800 million .

Mercor Funding Overview By CREDX Media

Startup Name	Mercor
Founders	Brendan Foody, Adarsh Hiremath, Surya Midha
Founded	2023
HQ	San Francisco, USA
Round	Series D Funding
Amount Raised	$750M
Valuation	$20B
Category	AI Data, Enterprise AI Evaluation, Human Feedback
Key Investors	Benchmark, Felicis, General Catalyst, NVIDIA, Salesforce, Sapphire Ventures, Apollo, Zoom
Total Funding (Latest Two Rounds)	$1.1B (Series C + D)
Employees	700
Contractor Pool	~30,000 active (5M+ vetted)
Annualized Revenue	$2B+ gross billings
Key Acquisitions	Deeptune (training environments)

💡 Use of Funds

• Research & Evaluation Infrastructure: Building realistic environments where agents can learn professional workflows.
• Post-Training Capabilities: Expanding the ability to train agents on enterprise-specific operations .
• Enterprise Expansion: Moving beyond supplying data to frontier labs and into helping enterprises build AI systems that understand their own operations .

Startup Overview: Mercor

What Mercor Is Building in Simple Words

Mercor has built a marketplace that connects AI companies with human experts—doctors, lawyers, engineers, accountants—who train and evaluate AI models on professional tasks. The company vets candidates, matches them to tasks, and manages the workflow of human feedback at scale.

But Mercor is now expanding beyond supplying training data. With this funding, it is building enterprise-specific evaluations—customized tests that measure how well an AI agent performs against a company’s own standards, on its own software, with its own policies.

• Human Expert Network: Over five million vetted experts, with about 30,000 in the active rotating pool .
• Customized Evaluations: Benchmarks built from actual enterprise workflows to show where post-training is needed .
• Realistic Training Environments: Through its acquisition of Deeptune, Mercor can recreate hundreds of enterprise applications where agents practice complex workflows before deployment .
• APEX Benchmark: Mercor’s public benchmark series measuring AI performance on economically valuable professional work .

Why Mercor Matters

• Frontier labs are no longer the only buyers: Sapphire Ventures’ Jai Das noted that frontier labs have so far been the main buyers of expert-driven training data, and enterprises will now want to evaluate and train agents on their own work .
• Generic benchmarks aren’t enough: Co-CEO Adarsh Hiremath framed the problem: “Every company deploying AI needs to know whether it works, and the answer is different for each one” .
• The market is huge and competitive: Mercor competes with Scale AI, which raised $1 billion at a nearly $14 billion valuation in 2024 before Meta invested $14.3 billion for a 49% stake, and Surge AI .
• Revenue is real: Over $2 billion in annualized gross billings, with net revenue estimated at $600-800 million, puts Mercor among the largest AI data companies in the world .

Founder Background: The Thiel Fellows Building the AI Data Layer

Brendan Foody and Adarsh Hiremath are Thiel Fellows who founded Mercor in 2023 alongside Surya Midha. All three were teenagers when they started the company, having met through debate competitions and dropped out of college to build Mercor .

Foody’s framing of the opportunity: “Every job in the economy will need its own AI agents, and every company will need a way to train and evaluate them on its own work” .

Hiremath added: “Every company deploying AI needs to know whether it works, and the answer is different for each one” .

Founder Intelligence: What Founders Can Learn from Mercor

• Start with the customers who pay first: Mercor built its business serving frontier AI labs, who needed expert data and were willing to pay for it. That revenue funded expansion into enterprise, where sales cycles are longer but the market is larger.
• Expand along the value chain: Mercor moved from supplying training data to building evaluations to creating training environments. Each step increased the value it delivers and the moat it builds.
• Acquire for capability, not just customers: The Deeptune acquisition gave Mercor teams who had already recreated hundreds of enterprise applications as training environments. Buying capability can be faster than building it.
• High revenue ≠ high margin: Mercor’s $2 billion gross billings with contractors keeping 60-70% means net revenue is much lower. Transparency about this distinction matters for investors and the market.

Investor Intelligence: Why This Round Gets Premium Capital

Benchmark, General Catalyst, and Sapphire Ventures participated, bringing deep enterprise and AI expertise.

Jai Das, President and Partner at Sapphire Ventures, framed the thesis: “Mercor has built something hard to replicate… We’re thrilled to partner with Brendan, Adarsh, and team to help them scale in the Enterprise market” .

NVIDIA and Salesforce participated strategically. Their backing signals that major AI infrastructure and enterprise software companies see Mercor as critical to the agent economy .

The investor roster—spanning venture capital, strategic corporates, and financial institutions like Apollo and StepStone—signals conviction across multiple dimensions of the market .

The Road Ahead for Mercor

Expansion Targets

With $750 million in capital, Mercor will:

• Build enterprise-specific evaluations at scale .
• Expand post-training infrastructure, including realistic environments where agents learn professional workflows .
• Grow beyond frontier labs into Fortune 500 enterprises across industries .

The Competitive Landscape

Mercor operates in a market with well-funded competitors:

• Scale AI raised $1 billion at a nearly $14 billion valuation in 2024, then received a $14.3 billion investment from Meta for a 49% stake .
• Surge AI is another major player in specialized AI training data and human feedback .

Mercor’s differentiation is its breadth of expertise (over 5 million vetted experts), its evaluation infrastructure, and its expansion from data supply into enterprise AI deployment .

Conclusion

Mercor’s $750 million Series D at a $20 billion valuation validates the thesis that every enterprise will need a way to train and evaluate AI agents on its own operations. The company’s $2 billion gross billings, five million vetted experts, and Deeptune-powered training environments position it as a critical layer in the enterprise AI stack.

Market tailwinds favor Mercor: the explosion of AI agent deployments, the inadequacy of generic benchmarks, and the willingness of enterprises to pay for evaluation infrastructure that reduces deployment risk. Whether Mercor can convert its data supply business into a durable enterprise platform—and compete with Scale AI’s Meta-backed scale—remains to be proven. But the company has the capital, the customers, and the thesis to try.

For deep analysis of AI funding, enterprise evaluation infrastructure, and companies reshaping how AI agents are trained and tested, explore CREDX Media for comprehensive coverage of startup funding trends, valuation intelligence, and founder playbooks.

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Frequently Asked Questions

1. What is Mercor’s total funding and latest round size?
Mercor has raised **$750 million** in Series D funding at a $20 billion valuation, following a $350 million Series C at $10 billion in October 2025 .

2. How much did Mercor raise in its Series D round and who led the investment?
Mercor raised $750 million with participation from Benchmark, Felicis, General Catalyst, NVIDIA, Salesforce, Sapphire Ventures, Apollo, Zoom, and others .

3. What is the valuation of Mercor?
Mercor is valued at $20 billion, double its valuation from about a year ago .

4. Who are the major investors in Mercor?
Major investors include Benchmark, General Catalyst, NVIDIA, Salesforce, Sapphire Ventures, Apollo, Felicis, Zoom, and StepStone Group .

5. Who are Mercor’s founders?
Mercor was founded in 2023 by Brendan Foody (Co-CEO), Adarsh Hiremath (Co-CEO), and Surya Midha. All three were Thiel Fellows who dropped out of college to build the company .

6. What is Mercor’s business model?
Mercor operates a marketplace connecting AI companies and enterprises with human experts for training and evaluating AI. It also provides customized evaluation infrastructure and training environments .

7. How does Mercor’s platform work?
Mercor vets experts, matches them to tasks, and manages human feedback workflows. For enterprises, it builds customized evaluations and realistic training environments using its Deeptune acquisition .

8. What traction justifies Mercor’s $20 billion valuation?
Mercor reported annualized revenue above $2 billion in July 2026 (gross billings), with net revenue estimated at $600-800 million. It serves frontier AI labs, technology companies, and Fortune 500 businesses .

9. What are Mercor’s plans for the $750 million Series D capital?
Mercor will accelerate research, evaluation, and post-training infrastructure, including realistic environments for agents to learn professional workflows, and expand into enterprise.

10. Who are Mercor’s main competitors?
Competitors include Scale AI (raised $1B at $14B valuation, later received $14.3B from Meta for 49% stake) and Surge AI .