ScienceAI Raises $50M to Build AI-Powered Scientific Research Assistant

The startup aims to accelerate scientific discoveries by helping researchers navigate the exponentially growing volume of scientific literature.

ScienceAI, a startup founded by former DeepMind and Google researchers, has raised $50 million in Series A funding to develop an AI-powered assistant for scientific research.

The platform, called Eureka, uses specialized language models trained on scientific literature to help researchers find relevant papers, summarize research findings, suggest experimental designs, and even identify potential gaps in current research.

"The volume of scientific literature being published is growing exponentially, making it impossible for researchers to stay current in their fields," explained Dr. Lisa Chen, CEO and co-founder. "Eureka helps scientists navigate this complexity and make connections they might otherwise miss."

The funding round was led by Sequoia Capital with participation from Andreessen Horowitz and several prominent scientists serving as angel investors, including Nobel laureate Jennifer Doudna and AI pioneer Yoshua Bengio.

ScienceAI's approach differs from general-purpose AI assistants by incorporating specialized knowledge of scientific domains and research methodologies. The system has been trained on millions of scientific papers across disciplines including biology, chemistry, physics, and medicine, with particular attention to understanding the nuances of scientific language and experimental design.

Early beta testers from universities including MIT, Stanford, and Oxford have reported that the tool helped them identify relevant research they had missed and suggested novel experimental approaches based on patterns in the literature.

"What impressed me most was Eureka's ability to connect findings across different subfields that don't typically cite each other," said Dr. Michael Zhang, a molecular biologist at Stanford who participated in the beta program. "It suggested a technique from materials science that we were able to adapt for our work in protein engineering, something we likely wouldn't have discovered otherwise."

The company plans to launch a public beta later this year, with special pricing for academic institutions. Their business model will include both subscription tiers for individual researchers and enterprise licensing for universities and pharmaceutical companies.

Industry analysts note that ScienceAI enters an increasingly competitive field of specialized AI tools for scientific research, with companies like Elsevier, Semantic Scholar, and others developing their own AI assistants for researchers. However, ScienceAI's focus on cross-disciplinary connections and experimental design suggestions may help differentiate it from alternatives that primarily focus on literature search and summarization.

The company has also emphasized its commitment to transparency in how recommendations are generated, allowing researchers to trace suggestions back to specific papers and understand the reasoning behind the AI's recommendations.