Autonomous AI for
Edge Privacy & Security
EnergenAI builds systems that detect, classify, and prevent covert data harvesting at the network edge — before your data ever leaves the building.
Three engines. One inference pipeline.
SENTINEL combines edge ML, behavioral analysis, and unified threat classification to protect networks without cloud dependency.
Edge ML Inference
On-device neural network models perform real-time traffic classification. No data leaves the local network. Sub-millisecond inference on constrained hardware.
Unified Threat Classification
Simultaneous privacy and security protection through a shared inference pipeline. Distinguishes manufacturer surveillance from third-party compromise of the same device.
Behavioral Baseline
Per-device communication profiling builds behavioral baselines. Detects anomalous exfiltration patterns, beaconing, and coordinated cross-device tracking in real time.
What we're building
From autonomous agents to privacy-first consumer applications, every product implements our patented edge inference architecture.
A self-operating AI agent framework running continuous inference cycles. Multi-provider cascade, autonomous content generation, and real-time threat analysis.
tiamat.liveInfrastructure & Partner Stack 9 integrations
Network appliance for autonomous detection and prevention of covert IoT data harvesting. ML-powered traffic classification with zero cloud dependency.
In developmentWellness tracking with on-device AI inference. Health data never leaves the phone. Reference implementation of our edge ML privacy patent.
Get it on Google PlayOn-phone traffic classification via Android VpnService. Quantized ML model classifies connection metadata without deep packet inspection. Zero root required.
In developmentFederal-ready from day one
Registered, patented, and structured for government and enterprise procurement.
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