Edison Scientific raises $70M to build autonomous AI scientists for research – News

Edison Scientific Inc., a San Francisco-based artificial intelligence startup building autonomous AI scientists to help accelerate scientific research, announced today that it has raised $70 million in new funding to expand its operations and development efforts.

Founded earlier this year as a spin-off from the nonprofit research organization Future House Inc., Edison Scientific is aiming to transform how scientific research is conducted by building and deploying autonomous AI systems that accelerate discovery. The company was launched to take the core AI research work developed at Future House and turn it into a sustainable, widely usable platform for scientific and industrial research.

Edison Scientific is developing an AI-powered research platform designed to automate entire segments of the scientific process that traditionally require large teams of human experts. The platform integrates capabilities such as literature synthesis, data analysis, molecular design, hypothesis generation and experimental planning into a unified environment.

The idea is that by integrating capabilities, researchers will be able to move more seamlessly from formulating a research question to generating validated results in far shorter timeframes than traditional methods.

The company’s main offering, called Kosmos, is an “AI Scientist” that can read thousands of scientific papers, run complex analyses, synthesize findings and generate fully cited reports in a single automated run.

Kosmos works by orchestrating specialized AI agents in parallel to maintain a structured world model that allows it to reason across large datasets and literature collections, essentially performing tasks that would otherwise take months of human effort in a matter of hours or days.

Edison Scientific’s platform also supports data-driven discovery workflows, including the ability to propose hypotheses, design computational experiments and help suggest next steps for wet lab validation. The features are particularly useful in fields like drug discovery, genetics and materials science, where rapid iteration over hypotheses and empirical findings can translate into real competitive advantage.

“Science is too slow,” explained Sam Rodriquez and Andrew White, the co-founders of Edison Scientific. “At Edison, we are integrating AI Scientists into the full stack of research, from basic discovery to clinical trials. We want cures for all diseases by mid-century.”

The seed round was led by Triatomic Capital LP, Spark Capital LP and a major unnamed U.S. institutional biotech investor, with Pillar VC LP, Susa Ventures Partners LP, Striker Venture Partners LP, Hawktail Management, Olive Tree Capital Advisors and a number of unnamed angel investors also participating.

Image: Edison Scientific