We're building the world's first autonomous structural intelligence platform for cybersecurity threat detection.
Enterprise security has become a "volume tax." Current SIEM and XDR solutions require companies to ship, store, and analyse massive amounts of raw log data in the cloud. As data volumes grow by 30% annually, security budgets are collapsing under the weight of cloud infrastructure costs.
Furthermore, these systems rely on "signatures" and "rules" — brittle logic that fails against novel, zero-day attacks.
We've developed a proprietary framework that moves detection logic from the cloud to the edge. Instead of looking for "bad events" (signatures), we monitor the structural geometry of your network.
By analysing the "habitual shapes" of human systems (Star, Tree, and Mesh topologies), we identify threats based on mathematical deviation, not historical rules. If an attacker moves, they change the shape of the graph. Our mathematics detects that change in milliseconds.
Our "edge-first" approach means customer data never leaves their environment. We process logs locally and only transmit 50-byte anonymised vectors to our cloud for calibration. Total privacy compliance (GDPR/CCPA) and near-zero cloud costs.
90% of office-based businesses share the same "structural DNA." We leverage this consensus to provide zero-configuration security. The system learns the global "healthy pulse" and pushes calibration weights to all nodes, creating a self-healing global immune system.
Because 99.9% of the compute happens on the customer's hardware, our gross margins are projected at >98%. We can scale to 100,000 customers with a fraction of the infrastructure required by incumbents like CrowdStrike or Splunk.
To make cybersecurity accessible, private, and effective by shifting from reactive event-based detection to proactive structural monitoring.