Beating AI News: Mirendil, founded by a former Anthropic researcher, announced a $1 billion Series A funding round led by Kleiner Perkins and Clearlake Capital, with participation from Google, Battery Ventures, and others. This comes in less than five months after its $200 million seed round earlier this year, bringing total funding to $1.2 billion.
According to informed sources cited by The Wall Street Journal, the company's valuation reached $5 billion in this round—five times that of the seed round—though the company has not officially disclosed its valuation.
Mirendil aims to use AI Agents to handle the entire R&D workflow of an AI lab. Last month, it unveiled an experiment: a single researcher using an AI Agent developed Mirendil-Base from scratch in just 3.5 months, with over 99% of the code written by the Agent and computing costs under $10 million. Subsequently, the company launched Fern, a model supporting up to 10 million tokens of context.
By late October, Mirendil also introduced Lor, a multi-Agent R&D platform designed to enable AI Agents to collaborate on model development. It can simultaneously orchestrate hundreds of Agents to write code, run experiments, automatically request and release GPUs, and operate continuously for days or even weeks. The company tested Lor by scheduling 102 Agents simultaneously to set up test environments for 100 code changes to PyTorch, averaging 8 minutes per task.
Mirendil hopes to offer this capability to external research teams, enabling scientists in fields such as drug discovery, materials science, and robotics to develop specialized models without needing to build large AI teams. Lor supports not only Mirendil’s own Fern model but also integrates with Claude, GPT, Kimi, DeepSeek, and other models. The platform is currently available only via invitation-only beta testing, free during the testing phase.