Mirendil, a frontier AI lab building systems that do AI research and development, has raised a $1 billion Series A led by Kleiner Perkins and Clearlake Capital. The company announced the round on November 12.
Battery Ventures, Doerr Capital, Gil & Co, Google, M13, Pear VC and S32 also participated, alongside other new and existing investors. Mirendil did not disclose a valuation.
Mirendil describes its mission as democratizing frontier AI R&D to accelerate science and technology. The lab trains frontier models specifically for AI research work and is redesigning how a lab operates around them, an approach it calls self-accelerating AI R&D.
Key facts
- 01Mirendil raised a $1B Series A led by Kleiner Perkins and Clearlake Capital, announced November 12, 2026.
- 02Battery Ventures, Doerr Capital, Gil & Co, Google, M13, Pear VC and S32 also participated.
- 03One researcher with agents pretrained Mirendil-Base from scratch in 3.5 months on under $10M of compute.
- 04Its Fern model supports up to 10M tokens of context; its Lor agent platform is in free, invite-only private beta.
Its first model, Mirendil-Base, is a competitive coding model. According to the company, a single researcher working with agents pretrained it from scratch in 3.5 months using less than $10 million in compute.
A second model, Fern, is post-trained with up to 10 million tokens of context, which Mirendil says is enough for days of an agent's work.
Both feed into Lor, an agent platform that entered private beta on October 28. Lor agents write code, run experiments and work for days, hundreds at a time, and they provision their own compute without requiring a cloud account. The platform runs on macOS, Linux and the web, with Windows, iOS and Android listed as coming soon.
Lor offers models from Anthropic, OpenAI, Google, xAI, Meta, Z.ai, Moonshot AI and DeepSeek alongside Fern. Access is by invite through a waitlist, and the platform is free during the beta.
Mirendil said it is still a small team and that the new funding lets it go further toward a world where one person can take on what used to need a team. The company has not named any public customers.
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