Lila Sciences Builds Scientific Superintelligence Through Autonomous AI Labs

New ventures in artificial intelligence are more than technology headlines—they're signals of scientific transformation and bets on fundamentally new ways of conducting research and accelerating discovery.​

Such funding announcements offer a glimpse into where science is headed, what investors are prioritizing, and how cutting-edge AI is making its way from concept to real-world application.​

In this series, we're covering early-stage AI and biotech companies that recently raised capital, spotlighting the technology—and the science—behind them. Next up: Lila Sciences.​

Lila Sciences' Bold Goal: Autonomous Scientific Discovery at Scale

Lila Sciences, a Cambridge, Massachusetts-based AI company, emerged from stealth in March 2025, according to company announcements, with an audacious mission: to build the world's first scientific superintelligence platform paired with fully autonomous laboratories. The company was founded within Flagship Pioneering's labs in 2023 and operated in stealth mode for nearly two years before its public launch.​

The company is pioneering an advanced form of AI that goes far beyond processing data and making predictions—it can design and conduct experiments, generate hypotheses, and test them in automated laboratory environments with minimal human intervention. Lila refers to these facilities as "AI Science Factories," where robotic instruments controlled by specialized AI models run experiments continuously across life sciences, chemistry, and materials science.​

Why Traditional Scientific Discovery Needs Disruption

For decades, scientific progress has followed the same pattern: researchers in lab coats mixing chemicals, waiting for reactions, recording results, and slowly iterating toward breakthroughs. This manual, time-intensive process creates bottlenecks that delay discoveries in critical areas like therapeutics, sustainable materials, and clean energy.​

Many AI laboratories focus on training large language models using internet-based data—a resource that researchers have questioned the sustainability of. Lila's approach differs fundamentally: it emphasizes creating proprietary scientific data through novel experiments conducted in automated facilities. "If your training input is entirely publicly available data, then one hits a ceiling," said co-founder and CEO Geoffrey von Maltzahn. The company believes that future leadership in scientific AI will depend on owning the most extensive automated laboratory infrastructure, rather than merely operating the largest data centers.​

A Novel Platform: Closed-Loop Automation

Lila Sciences' AI Science Factories represent a closed-loop system where AI models generate hypotheses, design experiments, control robotic equipment to execute those experiments, analyze results, and then iterate. This approach positions AI as a discovery engine rather than merely a research tool, compressing research timelines that typically take years into months by running thousands of experiments in parallel across multiple domains.​

The platform combines specialized AI models trained on scientific data with physical automation infrastructure that can operate around the clock. Rather than commercializing discoveries directly, Lila operates as a platform and R&D partner, planning to offer access to its AI models and automated laboratories through enterprise software. This allows clients in energy, semiconductors, pharmaceuticals, and other sectors to accelerate their own research programs.​

Leadership & Expertise

Lila Sciences was founded by a team of experienced innovators including Noubar Afeyan, Geoffrey von Maltzahn, Molly Gibson, Jacob Feala, Alexandra Sneider, and Ben Kompa. The company has also attracted prominent scientists including George Church, a Harvard geneticist renowned for his groundbreaking work in genome sequencing, who joined as Chief Scientist.​

Geoffrey von Maltzahn, Ph.D., serves as Co-Founder and Chief Executive Officer. Von Maltzahn is a General Partner at Flagship Pioneering and brings extensive experience in launching transformative biotech companies, including Tessera Therapeutics, Generate Biomedicines, Sana Biotechnology, and Indigo Agriculture. He has articulated Lila's vision, stating that achieving "Scientific Superintelligence responsibly" is the most important opportunity of our time.​

The company leverages Flagship Pioneering's proven track record of originating and fostering over 100 scientific ventures, including Moderna.​

Funding & Backing

Lila Sciences' fundraising trajectory demonstrates exceptional investor confidence in autonomous scientific discovery.​

The company initially emerged from stealth in March 2025, announcing $200 million in committed seed capital. Investors in the seed round included Flagship Pioneering, General Catalyst, March Capital, ARK Venture Fund, Altitude Life Science Ventures, Blue Horizon Advisors, State of Michigan Retirement System, Modi Ventures, and a wholly owned subsidiary of the Abu Dhabi Investment Authority.​

In September 2025, Lila raised $235 million in Series A funding co-led by Collective Global and Braidwell, achieving unicorn status with a valuation of approximately $1.23 billion. Most recently, in October 2025, the company secured an additional $115 million extension to its Series A with participation from Nvidia's venture arm, bringing total Series A funding to $350 million and overall capital raised to $550 million. This latest funding elevated Lila's valuation to more than $1.3 billion—a remarkable achievement for a company less than two years old.​

The financing will enable Lila to accelerate development of its AI Science Factories and expand its laboratory footprint. The company recently signed a 235,500-square-foot lease in Cambridge, Massachusetts, marking one of Greater Boston's largest lab leases in 2025. Lila also plans to establish additional hubs in Boston, San Francisco, and London to execute scientific research at global scale.​

Platform Applications & Market Opportunity

Lila Sciences is positioning itself to serve multiple high-value markets simultaneously by offering platform access rather than developing end products. The company's autonomous laboratories and AI models have already attracted interest from enterprises in energy, semiconductors, and pharmaceuticals—sectors that face intense pressure to accelerate innovation while managing rising R&D costs.​

Unlike traditional contract research organizations or AI software vendors, Lila combines both computational intelligence and physical automation infrastructure. This integrated approach allows the company to generate proprietary experimental data across diverse scientific domains, creating a potential competitive advantage as the platform learns and improves through continuous operation.​

"We are not going to take molecules into clinical trials ourselves, nor will we scale new energy innovations," von Maltzahn stated in a Reuters interview. "These tasks will be undertaken by Lila's partners and startups utilizing the Lila platform.”​

The company claims its platform has facilitated thousands of discoveries and run hundreds of thousands of experiments across life sciences, chemistry, and materials, though it has not yet published peer-reviewed data supporting these claims. Among the reported achievements are gene therapy constructs, antibodies and peptides, non-platinum catalysts for green hydrogen production, and carbon capture sorbents.​

Looking Ahead

Lila Sciences is staking a claim to lead the emerging field of autonomous scientific discovery by combining significant capital, cutting-edge AI capabilities, and large-scale physical infrastructure. The company's vision extends beyond incremental improvements in research productivity to reimagining how the scientific method operates at scale.​

"It will initiate a new form of the scientific method," von Maltzahn stated, emphasizing that AI-driven discovery could benefit "nearly everyone on the planet". The company plans to open parts of its platform to external partners by late 2025 and is even planning head-to-head trials pitting human researchers against its AI systems.​

Success will depend on several factors: demonstrating that autonomous laboratories can consistently generate commercially valuable discoveries across multiple domains, building trust with enterprise partners who may be skeptical of fully automated research, and navigating the inherent complexity of scaling physical infrastructure alongside AI capabilities.​

The pursuit of AI in scientific discovery has become a focal point for venture capital, with investors wagering that specialized AI systems can unlock breakthroughs that traditional methods cannot achieve at comparable speed or scale. As Lila expands its laboratory footprint and refines its platform, the company's ability to deliver on its ambitious promise of scientific superintelligence will become increasingly visible to the research community and commercial partners alike.