At Undermind, we're building a search engine that can handle extremely complex questions. It’s geared at experts, like research scientists and doctors, who need to find very specific resources to solve high-stakes problems. We’ve rebuilt search from the ground up to address this. Our new approach employs high-quality LLMs to adaptively explore a database, mimicking how a human researcher carefully discovers information. This approach dramatically outperforms (by 10-50x) traditional keyword search and other modern AI-based retrieval methods. Our first target users are the 50 million researchers searching for scientific literature on PubMed and Google Scholar every month. We’ve launched and have users paying us $200-$1000 per seat per year, from fields like medicine, ML, biotech, finance, and more. Our techniques in the future can port to even broader use cases and databases in law/consulting/finance.
Undermind offers various pricing plans tailored to individual researchers, academic institutions, and corporate teams. Detailed pricing information is available on the website.
Undermind was founded by two quantum physics PhDs from MIT, bringing decades of deep research experience to the development of next-generation AI-powered search algorithms. The team is dedicated to supporting researchers with tools that augment their capabilities in the age of AI-powered scientific discovery.
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