Startups & Funding
Nous Research is finalizing at least $75 million in funding
Open-source AI startup Nous Research is finalizing a funding round of at least $75 million at a $1.5 billion valuation.
Nous Research, the startup behind the open-source Hermes AI agent, is finalizing a new funding round led by Robot Ventures, with significant participation from Union Square Ventures (USV) and other investors, at a $1.5 billion valuation, according to three sources with knowledge of the deal. The company is raising at least $75 million and has fielded a high level of investor interest, the sources said.
The round comes less than three months after Nous announced its $50 million Series A. Before this round, the company had raised a total of $70 million in funding from investors including Paradigm, Robot Ventures, North Island Ventures, OSS Capital, and Balaji Srinivasan, according to Crunchbase. Nous Research was founded in 2023 by Jeffrey Quesnelle, Karan Malhotra, Ryan Teknium, and Shivani Mitra.
The company’s product, Hermes, is an open-source AI agent that competes with OpenClaw, a rival agent that runs locally on a PC. On GitHub, Hermes has amassed roughly 214,000 stars and nearly 40,000 forks — stars mark how many developers have bookmarked the project, while forks count how many have copied its code to build on — a scale of activity that points to substantial developer adoption.
Sources say the new funding will help Nous Research expand Hermes products and its business model further. The open-source version of Hermes can be run for free on a desktop or a virtual private server, while Nous also operates a separate decentralized network for contributing hardware compute and training. Beyond that, the company sells a cloud-hosted version of Hermes through paid tiers ranging from $20-$200 a month for users who prefer not to set the agent up on their own machines.
Why it matters
The rapid valuation surge of Nous Research highlights the intense investor demand for open-source AI agents that offer local execution and flexible, decentralized alternatives to proprietary models.