TraceMind acts as an automated network diagnostic analyst built directly into the core of Signal Vault. It removes the need for configuring complex rules and manual query correlation. It scans flow metadata continuously, using on-premise AI models, so you know exactly what is happening in your network without risking privacy.
By running local Large Language Models (LLMs) on raw packet metadata, TraceMind bridges the gap between deep telemetry facts and readable operational diagnostics.
TraceMind scans your active traffic stream and logs. It monitors every network endpoint connection continuously, flagging suspicious activity and abnormal metrics instantly. No manual queries required.
The dashboard status indicator updates automatically as packet metrics refresh. Operations teams receive live visual cues of network health and potential threats without reloading pages.
TraceMind processes live streams from active network multimeters. It also works offline, permitting network and performance engineers to upload CSV files, flow exports, and parsed log databases for forensics.
Produces a complete analysis layout: count of connections scanned, number of anomalies flagged, and a readable detailed log of flagged connections. Easily search and filter by IP, port, and protocol.
Runs on local infrastructure. Your network architecture, host IPs, internal protocols, and traffic patterns never leave your secure perimeter. Complies with local data governance policies.
Provides detailed information for flagged connections: source, destination, protocol, timestamp, packet count, byte size, and natural language explanations for anomaly classifications.
Unlike standard SaaS monitoring platforms that transmit packet logs to public cloud LLMs, TraceMind's architecture utilizes a locally compiled lightweight LLM. The intelligence lives where the data lives. No external routing modifications, no third-party cloud data-processing agreements.
