Mirendil Secures $1.2 Billion in Funding in Under 5 Months; Its Valuation Reportedly Surges Fivefold, Aims to Use Agents to Take Over AI Labs.

Insight Beating AI Flash News: Mirendil, founded by a former Anthropic researcher, has closed a $1 billion Series A funding round led by Kleiner Perkins and Clearlake Capital, with participation from Google, Battery Ventures, and other investors. Less than five months after its $200 million seed round in June this year, the company’s total funding has reached $1.2 billion. The Wall Street Journal, citing sources familiar with the matter, reported that the current round values Mirendil at $5 billion, five times its seed round valuation, though the company has not officially disclosed its valuation. Mirendil’s goal is to use AI agents to handle all R&D work for an AI lab. Last month, it unveiled an experiment: a researcher, working with AI agents, pre-trained Mirendil-Base from scratch in just three and a half months, with over 99% of the code written by agents and a compute cost of less than $10 million. Shortly after, the company launched the Fern model, which supports a 10 million token context window. At the end of October, Mirendil also rolled out Lor, a multi-agent R&D platform designed to let AI agents collaborate on model development. The platform can schedule hundreds of agents simultaneously to write code, run experiments, automatically allocate and release GPUs, and operate continuously for days or even weeks. Mirendil also tested Lor’s capability to schedule 102 agents at once to set up test environments for 100 PyTorch code modifications, with an average of 8 minutes per task. Mirendil aims to make this technology accessible to external research teams, allowing scientists in fields like pharmaceuticals, materials science, and robotics to develop specialized models without building large in-house AI teams. In addition to supporting its own Fern model, Lor can integrate models from Claude, GPT, Kimi, DeepSeek, and others. The platform is currently in an invitation-only beta testing phase, with free access during the test period.