Radically better research, radically faster
Our AI assistant carefully reads hundreds of academic papers for you, finding exactly what you need, no matter how complex.
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An Intelligent Assistant
Imagine having a personal research assistant.
You could devote hours of careful research to every problem, idea, or question you have. You'd have the very best knowledge and solutions at your fingertips.
Now, with intelligent language models, it's possible.
Incredibly complex topics
You can describe exactly what you want to Undermind, as if to a colleague.
Accurate results
Undermind finds the precise papers you need, with clear explanations about why they matter.
Comprehensive discovery
Undermind reads hundreds of papers, intelligently adapting as it goes. It knows when it's found everything.
Brainstorm with a copilot
Undermind helps you find the most important questions to ask.
What Researchers Say
"Undermind’s unique, high-powered search and synthesis algorithms give me exactly the information I need, and it’s come through for me at many crucial moments in my technical work. Along with many others on our team, I’m a paying subscriber, and I think anyone searching the scientific or technical literature should be using this incredible tool."
"Undermind is easily the best lit search tool out there. My team and I have been using it for months and are now long-term subscribers. It does what ChatGPT can’t: gives you precise examples from which it synthesizes a thorough summary, even for highly specialized and complex research topics. It’s had a huge impact on our work, for example by helping us quickly identify the right mouse models to test our immune-modulating drugs, saving us potentially months of troubleshooting."
"I’ve been using Undermind along with my team and we love this product. It’s amazing how it can dig up obscure papers that would take days or weeks to try to find otherwise. It’s incredibly valuable because it directly provides precisely the information you need. I’ve had our whole R&D team at Actipulse set up with subscription access for a while now and we are thrilled with it!"
Next Generation AI-Powered Search Algorithms
Undermind isn't like other search engines. Instead, we reimagined search from the ground up in order to mimic a human's careful, systematic discovery process. During each search, we examine results in stages, and use language models to make key decisions, such as recognizing crucial information and adapting the search strategy. This leads to unprecedented accuracy and comprehensiveness.
We benchmarked the first version of Undermind to be 10-50x better than Google Scholar, and we've been improving ever since.
Learn MoreSolve Real, Complex Problems
Frequenty Asked Questions
If a search takes less than 30 seconds, it can't possibly be this good.
Every other "search engine" you've used really just returns recommendations, not precisely relevant results. If you're asking for something general or something that's common knowledge, that's sufficient, since most of the results will be helpful. However, that's not what scientists need. For researchers, what you need is often so complex that you have to wade through hundreds of results. It's painful.
You should think of Undermind as sending a talented colleague to search for you, who will carefully, thoughtfully filter through papers to find exactly what you need.
Another possibility is that the Undermind search has not yet converged. Unlike in a traditional search engine, where all results are returned at once, ordered from best to worst, we perform a search in stages, like you would as you carefully search the literature. We look at a the most promising set of papers first, and depending on the difficulty of finding relevant results within these papers, we may not discover all the relevant papers in this first pass. By statistically modeling this process, we can determine what fraction of relevant papers we have likely found. If your paper didn't show up at first, it's likely the search system knows it has not yet found everything (and the report summary will tell you). You can deploy more computation ("extend" the search) to find the rest. See our whitepaper for additional explanation.
Started by two quantum physics PhDs from MIT, with decades of experience in deep research.