Post-quantum infrastructure for AI agents. Private data. Verifiable actions. Cryptographically enforced.
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Joined August 2025
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The launch is just the beginning!
Now it's time to see OpenMatter in action.
Datavizor is the command center for deploying, monitoring and verifying cryptographic compute across the OpenMatter Network.
Whether you're building AI, analytics or secure data collaboration, Datavizor is where it starts.
Launch your first deployment:
datavizor.openmatter.network…
Most platforms for running AI agents make you sign up, or book a call, before you can see the console.
Datavizor has a button on its login dialog labeled "Just let me play!" It opens a sample workspace with every screen unlocked. No account, no card.
Here's the tour. 🧵
Stop four: Collaborate. It runs Masked Compute sessions, where several organizations train a shared model without handing over their data.
Each participant's data stays on its own machine, and five independent servers compute over masked pieces.
When you want a workspace of your own, Sign Up for Free puts you on the Explore plan with 25 compute credits a month. No new password, no credit card.
Press play: datavizor.openmatter.network…
The full tour: openmatter.substack.com/p/pr…
This week's Industry Updates: a crew ran 1,100+ AI-agent attack projects from control panels anyone could open, and India says AI labs' test agents reached live systems unnoticed.
Also: an OpenAI model paying with a stranger's test wallet, and Germany's 2030 deadline. 🧵
Story 5: In a Booz Allen lab built like a manufacturing plant, frontier AI models went from a break-in at the network edge to the control network that runs the machinery in just over 16 minutes.
Humans approved every exploit and any action with a physical effect.
Story 6: Germany wants high-risk systems on post-quantum encryption by 2030.
Its cyber agency also advised against Classic McEliece in new systems. Research points to weaker security than assumed, though no practical attack is possible yet.
Full issue: openmatter.substack.com/p/op…
Running an AI agent on sensitive data takes six things: private compute, keys the agent never holds, limits on where it can go, a checkable record, post-quantum encryption, and one place to run it.
Each is sold as a separate tool. Here's why we built them as one platform. 🧵
Masked Compute trains a shared model without anyone handing over their data. Each row is split into five masked pieces, one for each of five servers.
MatterChain records each policy's hash and the agreement on every joint result.
All of it runs from Datavizor, with one sign-in.
Start here: datavizor.openmatter.network…
The full article: openmatter.substack.com/p/wh…