AI research assistant for source-grounded document analysis | Helping researchers and teams to build clarity from the chaos of complex knowledge

San Francisco, CA
Universities can't let their researchers and students use AI on academic documents because nothing they get back is verifiable or governed.
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Sharly is source-grounded AI for documents that institutions can deploy campus-wide with admin control.
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Most AI tools can't be cited. They don't show where an answer came from, and there's nothing for a reviewer to check.
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Sharly is built for the methods section: passages you can verify, and a technical note with a DOI describing exactly how it works, limitations included.
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Dozen published papers, theses and preprints already refer to Sharly — but there was no canonical way to cite it.
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Now there is: a technical note with a DOI, plus every one of those works listed with its link.
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Journals require you to disclose any AI tool you used. Most researchers have no idea how to word it.
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So we wrote the sentence for you, and gave Sharly a DOI so you can cite it properly.
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Sharly is now citable.
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A technical note on Zenodo describes how it works, what it does, and its limits — with a DOI you can put in your reference list.
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New in Sharly: paste a DOI or arXiv ID directly — no need to turn it into a URL first. Examples: 10.1038/nature12373 arXiv:2101.00001
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Sharly now recognizes the identifier, resolves it automatically, and uploads the paper.
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Small improvement. Much smoother research workflow.
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Dropped a 200-page PDF into Sharly this morning. Got clarity back before the coffee was done brewing
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🚀 1M users in year one. In this podcast, I share how @SharlyAI scaled fast & stayed focused: hyperengage.io/podcast/ep-15…
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Ask. Understand.
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Intelligence is becoming a utility. Sharly lets you plug into it.
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🎓📷 Excited to see @MineduPeru taking about AI and showcasing Sharly in action: helping researchers automate literature review, compare academic factors, and boost productivity.
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