Every researcher has done this:
Asked ChatGPT for verified references on a technical question. Got 10 papers that looked perfect. Real-sounding titles. Real-sounding authors. Real-sounding journals.
Then you tried to verify them.
6 don't exist. 2 have the wrong authors. 1 is from a journal that was never published. The last one is real but says the opposite of what ChatGPT claimed.
You just wasted 45 minutes fact-checking an AI that confidently lied to you. And you're back to doing the literature review manually.
This is the single biggest problem with using AI for research. The models are trained to sound right, not to be right. They generate plausible-looking citations the same way they generate plausible-looking code. Sometimes it works. Sometimes it's fabricated from scratch.
Someone finally built a tool where this is structurally impossible.
Mimir searches millions of real scientific papers. It reads them. It understands your question in plain language. And it returns a cited answer where every single reference is a verified, real publication.
Not "probably real." Not "we tried to check." Architecturally impossible to hallucinate.
The system indexes actual papers, books, patents, and industry reports. It can only cite what exists in its corpus. If a paper isn't real, it can't appear in your results. The architecture won't allow it.
Ask a complex technical question. Get an answer with 10 verified references in seconds. Each citation links to the actual paper. Real title. Real authors. Real journal. Real data.
What it covers right now: materials science, chemistry, physics, engineering. Expanding into new domains continuously.
What used to happen: 2 days reading papers, cross-referencing citations, verifying sources, discovering half your references are garbage.
What happens now: ask a question. Get a cited answer. Every reference is real. Move on.
Founded by a materials scientist and a computer scientist who spent too many years on the wrong side of this problem. They built Mimir because they've been the person spending two days answering a question that should take minutes.
1,000 researchers already using it.
Free for .edu and .gov emails.