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).
YantrikDB is a persistent cognitive memory database for AI agents: semantic recall, a knowledge graph, temporal decay, consolidation, and review of recognized structured conflicts. Run it as an embeddable engine (Rust or Python), an MCP server, or a replicated network service. Apache-2.0.
I built YantrikDB after repeatedly watching capable agents lose the thread between sessions. The first version solved persistence. That turned out to be the easy part.
Memory also needs boundaries, history, and a lifecycle. It should be possible to ask why a record surfaced, distinguish an old claim from a current one, keep tenants isolated, and preserve conflicting evidence without silently deleting either side.
YantrikDB now ships as one open-source engine you can reach four ways: Rust, Python, MCP, and a network server. The site includes an in-browser WebAssembly lab, a multi-agent example, published retrieval measurements, and the failure report for a conflict detector we deleted after it measured 0/16 precision.
The most useful feedback for me is concrete: where does your agent's memory fail today? Missed recall, stale context, namespace leakage, false conflicts, or something else? We also opened a Memory Failure Clinic for small synthetic reproductions, so uncomfortable cases can become public tests instead of vague claims.
YantrikDB is Apache-2.0. I would love your questions and hard failure cases.
No comment highlights available yet. Please check back later!
About YantrikDB on Product Hunt
“Memory that just works for AI agents”
YantrikDB was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #123 on the daily leaderboard. YantrikDB is a persistent cognitive memory database for AI agents: semantic recall, a knowledge graph, temporal decay, consolidation, and review of recognized structured conflicts. Run it as an embeddable engine (Rust or Python), an MCP server, or a replicated network service. Apache-2.0.
YantrikDB was featured in Open Source (68.9k followers), Developer Tools (519.8k followers) and Artificial Intelligence (479.1k followers) on Product Hunt. Together, these topics include over 223k products, making this a competitive space to launch in.
Who hunted YantrikDB?
YantrikDB was hunted by Pranab Sarkar. 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 YantrikDB stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Pranab Sarkar