Scientific research is drowning in data but starved of time. Labs generate vast datasets and face an ever-growing firehose of new papers. Yet much of the day is still spent on manual literature reviews, fragmented tools, and trial‑and‑error experimental design. Edison Scientific wants to change that by giving researchers an AI “co‑scientist” that can read the literature, analyse data and help design experiments.
The San Francisco-based startup has raised a $70 million seed round at a roughly $250 million valuation, co‑led by Spark Capital, Triatomic Capital and a major US biotech investor, with angels including Google chief scientist Jeff Dean and CrowdStrike co‑founder Dmitri Alperovitch also participating.
Giving scientists a lab partner
Edison spun out of FutureHouse, a nonprofit AI biology lab founded in 2023 to build an “AI scientist” for fundamental research. CEO and co‑founder Sam Rodriques is a physicist and bioengineer known for work in brain mapping and transcriptomics. In contrast, co‑founder Andrew White has led several AI‑for‑chemistry projects, including ChemCrow and PaperQA.
At the core of Edison’s platform is Kosmos, an “AI scientist” that can run long research campaigns on a single question. Given a goal and one or more datasets, Kosmos iterates among data analysis, literature search, and hypothesis generation, then returns a fully cited research report that some users say compresses months of work into a single day.
Around Kosmos, specialised agents handle tasks such as literature synthesis, molecular design, and precedent search, all accessed through a unified environment that integrates with existing lab data and workflows. Early projects include identifying therapeutic targets, mapping complex molecular structures and narrowing down promising candidate molecules, to shorten the path from idea to run‑ready experiment.
Unlike Periodic Labs, Lila Science, and Chai Discovery, Edison helps scientists decide what to do next rather than owning the entire stack.
What’s next?
With roughly 30 employees today, Edison plans to use the new funding to hire across AI, biology, chemistry, and engineering, and to turn its early traction into a broader commercial rollout.
The roadmap includes making Kosmos more autonomous, deepening integrations with lab information systems and collaboration tools, and expanding the “assistant‑style” agents that handle specific tasks, such as data analysis or precedent searches.
