Autoscience, a San Mateo-based applied research lab, announced it has raised $14 million in seed funding to develop what it describes as the world’s first automated AI research lab. The round was led by General Catalyst, with participation from Toyota Ventures, Perplexity Fund, MaC Ventures, and S32.
The company is building a virtual AI laboratory composed of autonomous AI scientists and engineers capable of inventing, testing, and deploying new machine learning models without human intervention. Autoscience aims to address a growing challenge in artificial intelligence development: while compute and data are abundant, the human capacity to generate and evaluate new ideas has become the primary bottleneck.
With more than 2,000 machine learning research papers published weekly, Autoscience believes traditional research teams cannot effectively keep pace. Its platform is designed to continuously generate hypotheses, validate them through experimentation, and deploy improvements into production systems. The system combines automated scientists that explore algorithmic ideas with automated engineers that optimize and operationalize successful models.
Autoscience has already demonstrated early milestones. Its autonomous system produced what it says was the first peer-reviewed scientific paper authored by an AI system at an ICLR 2025 workshop. It also achieved a silver medal in the Kaggle Santa 2025 competition, competing against more than 3,300 teams, marking a first for a fully autonomous system in a live Kaggle event.
The company plans to use the funding to expand its platform among Fortune 500 and large private enterprises, particularly in high-stakes sectors such as financial services, manufacturing, and fraud detection. Its managed service deploys hundreds of automated AI researchers simultaneously, enabling continuous improvement of machine learning models at scale. The capital will also be used to grow its engineering team as it accelerates development of autonomous research capabilities.
KEY QUOTE:
“We’ve reached a point where human intuition is no longer enough to navigate the complexity of algorithmic discovery. We’ve built a research organization where the researchers are AI systems. We aim to compress a decade of machine learning research into months, unlocking new AI capabilities for scientists and forming a competitive edge for our customers.”
Eliot Cowan, CEO of Autoscience
“We believe Autoscience is tackling an increasingly important challenge in machine learning: the pace and scalability of experimentation. As research output continues to grow, teams are looking for ways to more efficiently test, validate, and translate new ideas into production systems. We’re excited about their progress in advancing autonomous R&D to scale that workflow.”
Yuri Sagalov, Managing Director at General Catalyst
