Enable agents to keep context & work across apps + sessions
Walrus Memory enables AI agents to operate reliably across apps and sessions, without losing context. Portable, verifiable, and fully controlled by you, it is the memory layer that lets agents handle complex workflows and coordinate using data they can trust.
Hey Product Hunt 👋,
I’m Abner, Community lead at Walrus Foundation.
If you’re building AI agents, you’ve probably run into the same problem: a session ends and the context goes with it. Agents forget what they’ve learned, repeat work, and start from zero more often than they should.
Most teams end up stitching together memory from databases, vector stores, application logic, and permissions. It works — until you need agents to share context, coordinate reliably, or carry state across tools and sessions.
That’s why we built Walrus Memory.
It’s a portable memory layer for AI agents. Wire in two calls: remember and recall. Your agents keep context, share knowledge, and build on previous work instead of resetting every time.
The goal is simple: memory that holds up in production.
We’re curious how others are approaching this problem.
How are you handling memory today? What’s been the hardest part? I'd love to hear your feedback in the comments.
About Walrus Memory on Product Hunt
“Enable agents to keep context & work across apps + sessions”
Walrus Memory launched on Product Hunt on June 4th, 2026 and earned 83 upvotes and 8 comments, placing #27 on the daily leaderboard. Walrus Memory enables AI agents to operate reliably across apps and sessions, without losing context. Portable, verifiable, and fully controlled by you, it is the memory layer that lets agents handle complex workflows and coordinate using data they can trust.
On the analytics side, Walrus Memory competes within Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how Walrus Memory performed against the three products that launched closest to it on the same day.
Who hunted Walrus Memory?
Walrus Memory was hunted by Abner Pinto. 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 Walrus Memory including community comment highlights and product details, visit the product overview.
Abner Pinto