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).
Product upvotes vs the next 3
Waiting for data. Loading
Product comments vs the next 3
Waiting for data. Loading
Product upvote speed vs the next 3
Waiting for data. Loading
Product upvotes and comments
Waiting for data. Loading
Product vs the next 3
Loading
Memora-Swarm
The TLS for autonomous agent state.
The AI giants run agent swarms on last-write-wins databases like Redis. Result? Silent state forks and swarm-wide memory poisoning (OWASP ASI06). You can't patch this with middleware. Memora replaces fragile DBs with a 3-layer mathematical engine: L1 CRDTs guarantee fork-free convergence. L3 ACFA uses Q16.16 fixed-point math to auto-ban equivocators without a central coordinator. L2 Epistemic logic detects when agents agree on a lie and forces human escalation.
The AI industry is racing to build smarter agents. I'm building the infrastructure that stops them from silently corrupting each other.
Today's swarms run on last-write-wins databases. One compromised agent poisons the fleet, and standard CRDTs just silently converge on the bad data.
I built Memora-Swarm to fix the physics. Based on my ACFA research, it uses Q16.16 fixed-point math to guarantee un-forkable state and auto-ban Byzantine actors—without a central coordinator.
But the core vision is a philosophical shift: Consensus does not equal authority. If 100 agents mathematically agree on a stale fact, it's still a lie. Memora is the first state layer that refuses to act on agreed-upon untruths, escalating to humans when the swarm loses its grounding.
It's not another database. It's the immune system autonomous AI needs to actually deploy. The infrastructure agent swarms occupy.
About Memora-Swarm on Product Hunt
“The TLS for autonomous agent state.”
Memora-Swarm was submitted on Product Hunt and earned 15 upvotes and 9 comments, placing #71 on the daily leaderboard. The AI giants run agent swarms on last-write-wins databases like Redis. Result? Silent state forks and swarm-wide memory poisoning (OWASP ASI06). You can't patch this with middleware. Memora replaces fragile DBs with a 3-layer mathematical engine: L1 CRDTs guarantee fork-free convergence. L3 ACFA uses Q16.16 fixed-point math to auto-ban equivocators without a central coordinator. L2 Epistemic logic detects when agents agree on a lie and forces human escalation.
On the analytics side, Memora-Swarm competes within SaaS, Artificial Intelligence and Security — topics that collectively have 520.1k followers on Product Hunt. The dashboard above tracks how Memora-Swarm performed against the three products that launched closest to it on the same day.
Who hunted Memora-Swarm?
Memora-Swarm was hunted by Ryan Gillespie. 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 Memora-Swarm including community comment highlights and product details, visit the product overview.
Ryan Gillespie