Mercor S Verified

RL environment company · Multi-Domain

Domains: Multi-Domain Coding Enterprise Workflows Long-Horizon
On X: @mercor ↗
Funding: $450M raised · rounds and investors
Tier: S why
Snapshot: November 5, 2026

What Mercor does

Mercor runs a network of professional experts that supplies human data, evals, benchmarks and RL environments to frontier AI labs, licenses enterprise workflow data to labs, and deploys AI agents inside enterprises.

Sells: RL environments and Data
Leads with: Several domains (a generalist)
Based in: San Francisco, USA
Team: 250+
Website: mercor.com ↗

What Mercor sells

Read from Mercor's own website, checked October 12, 2026: the line that puts it in each category.

RL environments

Evals
“Build evalsEvaluate AI against professional standards”
mercor.com/ ↗
RL environments
“Benchmarks and RL environments built on real professional work (APEX).”
mercor.com/ ↗

Data

Human data
“30k+ experts: physicians, lawyers, engineers, consultants.”
mercor.com/ ↗
Datasets expanding into
“The data your business generates every day is exactly what frontier labs need. We license it, package it, and pay you for it.”
mercor.com/data/ ↗

Also

Enterprise AI services expanding into
“Deploy production AI with embedded Forward Deployed Engineers and enterprise-grade integrations.”
mercor.com/ ↗

Domains Mercor covers

Enterprise work
“Long-horizon, cross-application tasks in professional services”
mercor.com/ ↗
Finance
“Long-horizon, cross-application tasks in professional accounting”
mercor.com/ ↗
Coding
“Real-world software engineering across integration and observability”
mercor.com/ ↗
Health and bio
“Clinicians Survey – Ambulatory & Community Care Insights”
mercor.com/ ↗
Legal
“Contracts, case files, discovery docs”
mercor.com/data/ ↗
Science
“Applied Physics Benchmark Specialist”
mercor.com/ ↗

Benchmarks Mercor built or runs

APEX built it
“the AI Productivity Index (APEX), Mercor’s family of benchmarks that measure economically valuable capabilities”
mercor.com/blog/introducing-apex-agents/ ↗
APEX (AI Productivity Index) v1 / APEX-1 ↗ built it
“Each benchmark tests a different dimension of professional capability. All tasks are built with Mercor experts and leading industry partners.”
mercor.com/apex/ ↗

Mercor competitors and alternatives

The companies that sell the most of the same things in the same domains, and what they share with Mercor.

AfterQuery Also sells human data, RL environments and evals · also in coding, enterprise work and finance
ReasonCore Also sells RL environments, evals and human data · also in science, health and bio and coding
Turing Also sells human data and RL environments · also in coding, enterprise work and finance
Vetto AI Also sells RL environments, evals and human data · also in science, health and bio and legal
Align AI Also sells RL environments, human data and evals · also in legal, enterprise work and health and bio

Every RL environment company on the landscape map →

Tier S

Category leader: 200+ people, $100M+ raised or a $1B+ valuation.

How much stands behind a tier: usage, who backs it, a confirmed line from its own site or paper, and a clear read on X. High with three of the four, medium with two, low otherwise.

team 250+
raised $492M
valued $10B
investors: Felicis Ventures, Benchmark, General Catalyst
in curated RL directories (5 pts)

On X · unclear, low buzz, from 10 posts about Mercor in the last month

Posts are mostly gig workers sharing Mercor earnings, referral-style job promotions and rejection questions; nothing from AI labs or customers on data quality.

@TheOnimoleLagos ↗ · @MdrBwl ↗ · @arpitatscale ↗

How we got to tier S

Adoption: team 250+; raised $492M; valued $10B; investors: Felicis Ventures, Benchmark, General Catalyst. Tier S.
On X: unclear, low buzz. “Posts are mostly gig workers sharing Mercor earnings, referral-style job promotions and rejection questions; nothing from AI labs or customers on data quality.” No move.
In curated RL directories: 5 points, a floor of C.
Confirmed: a line from its own site or paper places it.

A clear view on X moves a tier one step up or down; most entries don't move. How tiers work.

Mercor funding

Raised: $450Msum of the rounds below
Latest round: Series C $350M2025-10 · led by Felicis
Valuation: $10B2025-10

Backed byFelicisBenchmarkGeneral CatalystRobinhood VenturesDST Global PartnersMenlo Ventures

Rounds

Series C · $350M at a $10B valuation · 2025-10 · led by Felicis
Today, we're announcing our $350 million Series C funding, led by Felicis with participation from Benchmark, General Catalyst, and Robinhood Ventures. This round values Mercor at $10 billion, 5x our Series B valuation.
1. Read: “Today, we're announcing our $350 million Series C funding, led by Felicis with participation from Benchmark, General Catalyst, and Robinhood Ventures. This round values Mercor at $10 billion, 5x our Series B valuation.”
2. Found word for word on its own site: mercor.com/blog/series-c
3. The quote states the amount and who led it
4. Also named by 3 other pages read
mercor.com/blog/series-c/
Series B · $100M at a $2B valuation · 2025-02 · led by Felicis
Felicis Ventures, which led the company’s previous $100 million Series B at a $2 billion valuation, is also leading this round.
1. Read: “Felicis Ventures, which led the company’s previous $100 million Series B at a $2 billion valuation, is also leading this round.”
2. Found word for word on a page found by search: techcrunch.com/2025/10/27/mercor-quintuples-valuation-to-10b-with-350m-series-c
3. The quote states the amount and who led it
4. Also named by 1 other page read
techcrunch.com/2025/10/27/mercor-quintuples-valuation-to-10b-with-350m…

In talks, not closed

Funding round · $500M at a $20B valuation · 2026-07 in talks
Mercor, the AI data labeling firm founded by the world’s youngest self-made billionaires, is in talks to raise $500 million at a valuation of $20 billion, according to a source familiar with the fundraising.
1. Read: “Mercor, the AI data labeling firm founded by the world’s youngest self-made billionaires, is in talks to raise $500 million at a valuation of $20 billion, according to a source familiar with the fundraising.”
2. Found word for word on a page found by search: forbes.com/sites/richardnieva/2026/07/09/mercor-fundraise
3. The quote states the amount; no lead is named in it
4. No other page or directory names it yet
forbes.com/sites/richardnieva/2026/07/09/mercor-fundraise/

Funds 5

Felicis led a round
Named in the round quoted above.
Benchmark
Named in the round quoted above.
General Catalyst
Named in the round quoted above.
DST Global Partners
Our latest round was led by Felicis, with participation from General Catalyst, DST Global Partners, Benchmark, and Menlo Ventures
1. Read: “Our latest round was led by Felicis, with participation from General Catalyst, DST Global Partners, Benchmark, and Menlo Ventures”
2. Found word for word on its own site: mercor.com/blog/series-b
3. No other page or directory names it yet
mercor.com/blog/series-b/
Menlo Ventures
Our latest round was led by Felicis, with participation from General Catalyst, DST Global Partners, Benchmark, and Menlo Ventures
1. Read: “Our latest round was led by Felicis, with participation from General Catalyst, DST Global Partners, Benchmark, and Menlo Ventures”
2. Found word for word on its own site: mercor.com/blog/series-b
3. No other page or directory names it yet
mercor.com/blog/series-b/

Corporate investors 1

Robinhood Ventures
Named in the round quoted above.

Every figure is quoted from its own site, its accelerator or a funding announcement; a round's amount and lead appear only when its quote states them. Startup databases are never used as evidence. Checked 2026-10-11. How funding is checked.

Where Mercor sits

Its domain on the map, live. Hover a logo for its name; click to open it. Open it on the full map

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Latest from Mercor on X

@mercor ↗

Kimi K3.1 Pro from @Kimi_Moonshot debuts as the #2 open-weights model on APEX-Agents. Top 5 open-weights models on APEX-Agents (Pass@1): 1. DeepSeek-V4.1-Flash-1017: 69.8% 2. Kimi K3.1 Pro: 65.5% 3. Qwen 3.8-Max: 63.3% 4. MiMo V2.6 Flash RL: 57.4% 5. GLM-5.3: 56.6% The Kimi model family has gained nearly 30 points on APEX-Agents in five months. Kimi K2.7 Code (June): 37.6% Kimi K3 (July): 47.8% Kimi K3.1 Pro (October): 65.5% Congrats to the @Kimi_Moonshot team. See full leaderboard:
— mercor (@mercor) Nov 5, 2026
At Fireworks Forge today, Mercor's CEO @brendanfoody spoke on how Mercor turns open models into frontier specialists. The core idea is that training data has changed. In 2020 it meant crowdsourcing: SFT, RLHF and behavior cloning, done at scale by people with no particular expertise. Today, the data that moves frontier models comes from experts. They write the rubrics, unit tests and RL environments that teach a model to do real professional work. The same expert judgment also measures the results. Our APEX benchmarks test frontier models on real knowledge work. Professionals design the tasks and grade them against rubrics, so we can see where a model holds up on the job and where it falls short. Experts train the model, and experts check it. That's how an open model becomes a specialist. See the latest results at https://t.co/bNOwoNpuHp. Thank you to @FireworksAI_HQ for having us.
— mercor (@mercor) Nov 4, 2026
We're proud to have collaborated on a new benchmark built by @GoogleAI: Physical-Engineering's Last Exam (PLE). Physical engineers design the skyscrapers, power grids, and chip fabs we rely on, yet no existing benchmark tested whether AI agents could do that work end to end. Together with Google and practicing engineers, we built 85 long-horizon tasks across mechanical, electrical, civil, and structural engineering. On the private test set, all frontier models score below 50%: 1. Claude Opus 5.5: 48.3% 2. GPT 6 Astra: 45.8% 3. Claude Sonnet 5.5: 43.5% 4. Gemini 4 Argon: 40.6% 5. Claude Opus 5: 40.0% On the tasks we co-authored, the top agent satisfied 91% of individual constraints, but only 41.3% of its deliverable items passed every hard safety check. Learning how AI fails at physical engineering can help us improve future models and build a safer world. This benchmark is also an open competition. Bring your own agent setup and submit it for evaluation on our private test set at
— mercor (@mercor) Nov 3, 2026

More Multi-Domain RL environments

Multi-Domain AI benchmarks

Next: browse all environments. Entry from the RL Research daily scrape of public sources, 2026-11-05 snapshot.