Mercor is a venture-backed expert marketplace and AI-training-data company. It supplies RLHF data, evaluations and reinforcement-learning environments to frontier AI labs and enterprises, drawing on a professional expert network: the homepage cites 30k+ experts, and Mercor's Deeptune post claims more than five million. It started as an AI-recruiting platform, moved into human data and RL, bought Sepal AI (Feb 2026), and announced the acquisition of Deeptune (Jul 2026), which builds simulated enterprise-app 'training gyms'. It publishes the APEX family of professional-task agent benchmarks. Mercor says it reached $2B ARR in June 2026, despite a March 2026 supply-chain data breach.
Twelve licensed CPAs, with 5.5 years of experience on average, completed four month-end close scenarios and averaged 37%. Claude Opus 5 scored 100% on all 20 attempts, each in under 10 minutes. Cost was $0.21 per criterion met for the model versus $10.35 for the humans. The authors caution that the tasks cover only some accounting skills and exclude client communication and contextual judgment.
Why it matters: Adds human baselines to Mercor's benchmarks, which helps interpret their scores.
Mercor redesigned its eval compute scheduling with a dynamic scheduler using job queuing and admission control. It reports a 20x throughput gain, addressing bottlenecks from global capacity partitioning and underused providers.
Why it matters: A signal of eval-infrastructure maturity. The 20x figure is self-reported.
Version 1.1 adds three expert audits per task, a new judge model (DeepSeek-v4-Flash-0731) that penalizes 'scattergunning' (hedged multi-answer outputs), and MCP tool reliability fixes. Claude Fable 5.1 led at launch with 68.6% Pass@1. The dataset is mercor/apex-agents-v1.1 on Hugging Face.
Why it matters: Fixes a form of score inflation. Anyone citing APEX-Agents results should say which version they used.
Mercor RL-trained Qwen3.5-397B-A17B and Qwen3.6-35B-A3B using SkyRL for training orchestration, Harbor for environment management, Docker and MCP. The 397B model's Pass@1 rose from 16.11% to 27.29%. Code, weights and traces are released at github.com/Mercor-Intelligence/ApexAgents-SkyRL-Recipe and in the Hugging Face collection mercor/apexagents-skyrl-recipe. The authors write that 'algorithm choices mattered less than the data'.
Why it matters: Public evidence that Mercor's environments are used for RL training, not only evaluation. It also documents a compatible stack (Harbor, Docker, MCP).
Twelve product-clone tasks, including Calendly, Figma, HubSpot, Linear, Notion, Rippling, Shopify, Tableau, Zapier, Zendesk and Google Docs. Pass rates across 8 models ran from 74% (GPT-5.6 Sol) to 27% (GLM-5.2). Seven of the eight models scored lower on computer-use (UI) tests than on deterministic backend tests, by 7.6 points on average.
Why it matters: A long-horizon coding evaluation for SWE-agent environment buyers. The UI-versus-backend gap shows features can be implemented in code yet unreachable through the interface.
An agent benchmark for month-end close and bookkeeping across 10 simulated companies. A sample dataset is on Hugging Face (mercor/apex-accounting-harbor), the Archipelago eval harness is on GitHub, and the technical report is arXiv 2607.27189. At launch the top model (Claude Fable 5) scored 56.4%, and 58% of tasks were never fully solved by any model on any run.
Why it matters: Adds accounting to the APEX family, and the evaluation stack is open.
A secondary outlet summarizing financial documents reported by The Information. It gives H1 2026 revenue of about $614M (up ~70% YoY), about 91% from AI foundation-model companies, and gross margin of 27% in 2025 rising to 33% in Q2 2026. Roughly two-thirds of revenue goes to contractors.
Why it matters: Heavy concentration in frontier labs and thin margins matter for vendor-risk assessment. This is low-tier sourcing: an aggregator relaying The Information, which is paywalled and could not be opened.
Deeptune is a NYC company led by CEO Tim Lupo. It raised a $43M Series A led by a16z in March 2026, and Foody invested in that round personally. Deeptune has recreated hundreds of enterprise applications, from spreadsheets to Salesforce, as simulated environments for agent RL. Mercor was already a Deeptune customer. The team joins Mercor's NYC expansion, and terms were not disclosed (per SiliconANGLE).
Why it matters: Mercor adds an environment and simulation software layer to its expert task-and-verifier network, so it can sell environments and tasks together. This is its second RL-environment acquisition of 2026, after Sepal AI in February.
SiliconANGLE reported that Mercor was in early talks to raise at about a $20B valuation, double the $10B of its October 2025 Series C. Forbes (2026-07-09) also covered a fundraise, but the page returned 403, so the round size (the draft's ~$500M) and the investors could not be verified. No closing had been announced as of 2026-10-05.
Why it matters: A scale and momentum signal. Treat it as reported talks: $10B is still the last confirmed valuation.
Foody told Fortune the business went from a $1B revenue run rate to $2B ARR in the previous four months. Fortune names Anthropic and OpenAI as customers. Foody said all of the Mag Seven except Tesla are customers and that 'every frontier lab has expanded their relationship with us since the data breach'.
Why it matters: Suggests frontier-lab demand recovered after the breach. All figures and customer claims come from the company (Foody), not audited numbers.
Kevin Shiau joined as Chief Financial Officer. He previously held finance and operations roles at Tesla, where he says he helped build the battery-storage business, and earlier worked at First Solar, Citigroup investment banking and an early-stage AI robotics company.
Why it matters: A CFO hire from a large public company is a typical sign of preparing for later-stage financing and financial controls.
The blog index lists a Company post titled 'Update on Mercor security incident' dated 2026-06-25. The post body could not be retrieved (the link returned 404 on 2026-10-05), so its contents are not summarized here.
Why it matters: Buyers doing security due diligence should ask Mercor directly for this incident update and its remediation findings.
After Mercor disclosed on March 31 that it was hit through the LiteLLM supply-chain compromise, a hacker group claimed it had taken 4TB of data, including candidate profiles, PII, employer data, source code and API keys. Wired sources said Meta paused its contracts indefinitely. OpenAI told Wired it was investigating its exposure but had not paused or ended its contracts. Business Insider reported that five contractors had sued, and one suit reviewed by TechCrunch also names LiteLLM and Delve.
Why it matters: A material security and vendor-risk signal. Meta's current status as a customer is unconfirmed: Wikipedia calls the pause 'temporary' but gives no date for any resumption.