eBPF Sensors, Patented Algorithms, AI Agents
SEER Observability Platform
Canopus is the creator of SEER, a real-time network observability platform powered by eBPF and AI Agents, that helps network and security operations teams accelerate AI-informed decisioning by extracting contextualized intelligence from their infrastructure.
Cloud-Native eBPF Sensors
Canopus Cloud-Native eBPF sensors deliver high-volume, real-time telemetry at scale across physical, virtual, and cloud-native environments. SuperNetFlow sensors provide granular per-flow, per-application visibility from network traffic at scale. FlowPulse sensors extract process, filesystem, and network socket logs from run-time application states at the kernel level. Together, these sensors offer end-to-end infrastructure coverage across networks, servers, VMs, containers, and Kubernetes.
Network Observability Streams
Canopus' patented algorithms transform per-flow network attributes into decision-ready intelligence. Peer-reviewed and research-backed, these algorithms classify encrypted traffic and measure per-application experience across a wide range of use cases, including: Video & Live Streaming, Cloud & Mobile Gaming, Conferencing and OT Devices. By fusing telemetry with business context, these data streams are highly contextualized and tailored to specific business needs - enabling precise, actionable insights.
Security Observability Streams
Canopus' behavioral algorithms transform thousands of raw kernel-level events and logs into actionable behavioral evidence chains enriched with identity context. These data streams provide real-time application state monitoring, dynamic vulnerability exploitability, and AI-driven asset classification across VMs, Containers, and Kubernetes. Designed for seamless integration, these insights can be fed into existing observability platforms via OpenTelemetry, ensuring a unified and enriched security posture.
AI Agents Workflows
Canopus' AI agents automate tedious human workflows, allowing operations teams to concentrate on critical decision-making tasks. With Agentic workflows, the cognitive load of memory management, correlation, and parallel processing is significantly reduced. These agents are always-on and capable of detecting experience degradations across applications whilst identifying potential root causes; or prioritizing vulnerabilities within the application infrastructure. By transforming reactive workflows into proactive insights and reports, Agentic workflows empower teams to respond more effectively and efficiently.
Key Differentiators
Transforming Observability, Ready for AI
Current network observability tools are outdated, leaving network and security operations teams struggling with low-fidelity data, insufficient context, and inefficient workflows. After seven years of rigorous research and development, Canopus has developed a robust technology stack supported by multiple research publications and eight patents. Here is what's unique about us:
Cloud Native eBPF. eBPF is a groundbreaking technology that enables sandboxed programs to run safely within the linux kernel, a prime location for implementing observability, security, and networking. Our sensor technology has evolved over time, from DPDK to P4 and now to cloud-native eBPF. Unlike costly hardware probes, our eBPF sensors offer a lightweight, scalable alternative that can be deployed in hours, not weeks.
Tetragon Integration. Canopus FlowPulse agents seamlessly integrate with Isovalent’s open-source Tetragon, a powerful Kubernetes-aware security observability and runtime enforcement tool. Tetragon minimizes observation overhead, enables precise process tracking, and enforces policies in real time. Already using Tetragon? Our sensors can be deployed alongside the Tetragon agent and feed into our observability platform.
Encrypted Traffic Classification. Accurate application classification over the network is essential for demand forecasting, ensuring quality of experience, and defending against network threats. In addition to state machines, SNIs, DNS, and byte patterns, our transformer-based models leverage deep learning to analyze stochastic behavioural patterns, enabling real-time classification of encrypted traffic.
Experience over Netflow. For over 25 years, NetFlow has been the standard for extracting network insights—tracking flow endpoints, volumes, and timestamps from internet routers. Canopus SuperNetFlow builds on this and provides application-level intelligence, identifying traffic types and providers, while delivering real-time Quality-of-Experience (QoE) metrics, including video resolution, buffer stalls, gaming lag spikes, and conference stutters.
Run-Time Behavioral. In cloud-native environments, real-time, actionable intelligence is critical for effective security. However, most tools overwhelm security teams with a flood of alerts and events, making it difficult to focus on what truly matters. Behavioral run-time baselining ensures security teams can prioritize vulnerabilities and risks based on the actual run-time context of applications.
Agentic Interface. Canopus AI agents, built on cutting-edge frameworks like Crew, LlamaIndex, and Claude, automate repetitive and tedious tasks through autonomous workflows, reducing cognitive and memory load for human operators. With the Agentic UI, investigation teams can ask questions and gain insights directly—eliminating the need to sift through complex dashboards or manually maintain them
SEER Platform Integrates with Existing Solutions
General Platform Capabilities
General Platform Capabilities
Network Technology Support for Network Observability
- 5G and 4G Networks
- Broadband Networks
- Enterprise Campus Networks
- Multi-Cloud Networks
- Cloud-Native Networks
Infrastructure Support for Security Observability
- Bare-Metal servers
- Virtual Machines and Docker Containers
- Kubernetes: GKE, EKS, Openshift
External Integrations
- Integrate through Kafka real-time streams
- Integrate through Open Telemetry
- Parquet and CEF Support
- Integrates into Google Cloud Storage and Amazon S3 Buckets
- Native support for SQL columnar databases
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