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Tamis
Screen thousands of documents without reading them all
Tamis reads every document against your brief, shows the likeliest first and learns from each decision. A random audit then proves what is left in the unread pile. For systematic reviews, drug safety monitoring and contract due diligence.
Top comment
Hi everyone, I'm Olivier, and today I'm launching Tamis. I built it on my own, from Brittany in France. Some background: I did a PhD in data mining, then worked as a software engineer. For the past two years I've been freelancing on projects full of documents, and I kept meeting people stuck with the same job. A researcher with 3,000 abstracts to screen for a review. A drug safety team checking every new paper about their product. A lawyer going through 80 contracts before an acquisition. They all read everything, sometimes twice, because missing one document is the real risk. So Tamis doesn't decide for you. You describe what you're looking for in plain words. It reads every document, puts the likely ones on top and shows you the sentence behind its answer. You go through them and it learns from what you keep. When you think you're done, it draws a random sample from what you haven't read and you check it blind. That gives you an actual number for what you might still be missing. On a public systematic review of 3,425 records, reading 1,901 in this order was enough to find at least 99% of the included studies. On 80 public contracts, Tamis pointed to the exact clause sentence 96% of the time. You can try it without an account: the sandbox has three sample projects. If you like it, the code PRODUCTHUNT gives you 50% off Pro for your first 3 months. I'd love to hear from people who do this kind of screening for a living: what would make you trust a tool like this, or not?
About Tamis on Product Hunt
“Screen thousands of documents without reading them all”
Tamis was submitted on Product Hunt and earned 5 upvotes and 1 comments, placing #79 on the daily leaderboard. Tamis reads every document against your brief, shows the likeliest first and learns from each decision. A random audit then proves what is left in the unread pile. For systematic reviews, drug safety monitoring and contract due diligence.
On the analytics side, Tamis competes within SaaS, Legal and Health — topics that collectively have 58.2k followers on Product Hunt. The dashboard above tracks how Tamis performed against the three products that launched closest to it on the same day.
Who hunted Tamis?
Tamis was hunted by Olivier Cavadenti. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Tamis including community comment highlights and product details, visit the product overview.