cPacket AI is an AI-driven network observability capability set embedded within cPacket Networks' Unified Observability Platform. It transforms packet-level data into actionable insights for NetOps, SecOps, and CloudOps teams operating across hybrid and multi-cloud environments. The platform follows a pipeline model: high-fidelity packets are captured at speed and scale, enriched into clean flows and session metrics, analyzed by AI/ML engines to detect anomalies and correlate events, and then surfaced through existing workflows via open APIs and MCP (Model Context Protocol). Core analytical capabilities include: - Unsupervised baselining using AI/ML methods that automatically track tens of metrics per session without manual threshold configuration - Anomaly detection across latency, traffic volume, and protocol behavior for both performance and security use cases - Event correlation spanning NetOps (e.g., link degradation) and SecOps (e.g., beaconing) domains - Root cause analysis with traceable, packet-level evidence All insights are described as "explainable," meaning each finding is traceable back to underlying packet data rather than produced by an opaque black-box model. Users can provide input to add relevance context to identified anomalies. The platform supports bring-your-own LLM integration and connects to external tools via open APIs and MCP. Deployment options include on-premises, virtual, and cloud environments. Business outcome metrics emphasized include reduced MTTR/MTTI, improved service reliability, audit-ready evidence, and lower total cost of ownership (TCO).