This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
OAK.memory
Persistent memory for your AI, across sessions and tools
Stop repeating your context to AI. OAK.memory stores facts and their connections, combining vector search with graph traversal to recall related context across sessions. Connect supported AI tools through MCP, or build with the open-source engine. Start with cloud memory or run locally.
Hi Product Hunt! I'm Fredric, the maker of OAK.memory.
I built it because useful context kept getting lost between AI sessions. I wanted memory to be a reusable layer that I could connect to the tools I already use.
OAK.memory combines vector search with an associative graph: search finds relevant facts, then graph traversal brings back connected context. You can connect supported AI apps through MCP, use cloud memory, or build with the open-source engine and local setup.
I'd love feedback on the setup experience and the quality of recalled context. What would you want your AI to remember across sessions?
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About OAK.memory on Product Hunt
“Persistent memory for your AI, across sessions and tools”
OAK.memory was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #54 on the daily leaderboard. Stop repeating your context to AI. OAK.memory stores facts and their connections, combining vector search with graph traversal to recall related context across sessions. Connect supported AI tools through MCP, or build with the open-source engine. Start with cloud memory or run locally.
OAK.memory was featured in Productivity (664.6k followers), Developer Tools (522.3k followers), Artificial Intelligence (482.7k followers) and GitHub (41.5k followers) on Product Hunt. Together, these topics include over 434.1k products, making this a competitive space to launch in.
Who hunted OAK.memory?
OAK.memory was hunted by Fredric Cliver. 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 OAK.memory stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Fredric Cliver
Hi Product Hunt! I'm Fredric, the maker of OAK.memory.
I built it because useful context kept getting lost between AI sessions. I wanted memory to be a reusable layer that I could connect to the tools I already use.
OAK.memory combines vector search with an associative graph: search finds relevant facts, then graph traversal brings back connected context. You can connect supported AI apps through MCP, use cloud memory, or build with the open-source engine and local setup.
I'd love feedback on the setup experience and the quality of recalled context. What would you want your AI to remember across sessions?