Manex is a private AI memory for documents and team knowledge. Upload files, ask grounded questions, and preserve useful answers, corrections, and context as memory. It runs locally where supported, keeps data private by default, and lets teams create a shared brain without per-seat pricing.
Hey Product Hunt 👋
We built Manex because teams don’t just lose documents. They lose context.
A decision may live in a PDF, the correction in a chat, and the reason behind it in someone’s head. Manex helps turn documents, questions, corrections, and useful conversations into a private AI memory that can be searched and reused later.
A few things we care about:
- private by default
- local AI where supported
- grounded answers with evidence
- shared Team Brain workspaces
- simple pricing: $29/month for a team, or unlimited documents for an individual
Would love feedback from anyone who works with lots of documents, compliance material, client files, research, policies, or internal knowledge. I have 10 codes for Lifetime unlock. Please do use them and leave a message. Reach out if you need help or are late to get one.
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This nails a real pain point. When I was CTO scaling from 15 to 120 engineers, the biggest knowledge drain wasn't people leaving - it was context dying between conversations. Someone would figure out why a system was designed a certain way, explain it in Slack, and three months later the next person would make the same mistake because that context was buried. The private-by-default approach is smart too. Most teams I've worked with won't adopt knowledge tools if there's any friction around what gets shared externally vs kept internal. How does the correction preservation work in practice - can you override an earlier answer if circumstances change?
"Local / in-browser" is the part that matters most for files I can't upload to a third party. How big can the input get before the browser chokes — and is there a desktop or CLI version planned for the cases where the browser tab isn't the right surface?
The 'preserve corrections as memory' angle is the part most knowledge tools miss — the value isn't the original answer, it's the corrected one after a domain expert pushed back. I run into this constantly when teaching financial modeling (I have an Excel for Financial Modelling course on Udemy: https://www.udemy.com/course/exc...), where 80% of the value of a senior modeler's review is in the corrections, not the original draft. Most courses and team wikis throw that layer away. Curious whether Manex distinguishes between an answer and a correction in its memory layer, or treats them as equally weighted snippets?
About Manex on Product Hunt
“Preserve useful answers, corrections, and context as memory”
Manex launched on Product Hunt on May 4th, 2026 and earned 117 upvotes and 11 comments, placing #11 on the daily leaderboard. Manex is a private AI memory for documents and team knowledge. Upload files, ask grounded questions, and preserve useful answers, corrections, and context as memory. It runs locally where supported, keeps data private by default, and lets teams create a shared brain without per-seat pricing.
Manex was featured in Productivity (651.7k followers), SaaS (42k followers) and Artificial Intelligence (468.6k followers) on Product Hunt. Together, these topics include over 269.3k products, making this a competitive space to launch in.
Who hunted Manex?
Manex was hunted by Ravi Krishnan. 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.
Want to see how Manex stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ravi Krishnan