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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?
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.
On the analytics side, OAK.memory competes within Productivity, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.7M followers on Product Hunt. The dashboard above tracks how OAK.memory performed against the three products that launched closest to it on the same day.
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.
For a complete overview of OAK.memory including community comment highlights and product details, visit the product overview.
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?