ALERTS THAT MAKE A DIFFERENCE
Do you use OpenTelemetry?
Beemon integrates seamlessly with opentelemetry data via the opentelemetry collector. Just inject the data and wait for results.
Observability That Actually
Understands Your Business
The first monitoring platform powered by Graph Neural Networks that automatically learns your architecture, maps your data flows, and adapts to your users' behavior patterns-no configuration, no manual rules, just intelligent insights that evolve with your system.
The World's First Self-Learning Observability Platform
Cutting-Edge Technical Differentiators
Unlike traditional rule-based systems, our AI understands the relationships between services:
-> Dramatically reduced false positives through topology-aware analysis and business context understanding.
-> Learns your architecture automatically, continuously adapts to dependencies, user patterns, seasonality, traffic shifts, and evolving business rhythms without manual intervention.
-> Unified multimodal intelligence: single Graph Neural Network correlates traces, metrics, logs, infrastructure, and code changes.
-> Predicts failures 15-30 minutes early forecasts SLA violations and catastrophic failures before customer impact.
-> Intelligent contextual alerts: every notification includes confidence scores, business impact, and recommended actions.
-> Real-time intelligent diagnostics pinpoint root causes in seconds with full propagation paths and proof of causation.
-> Topology-aware by design. It automatically maps service dependencies, communication patterns, and failure propagation paths.
-> Learns YOUR patterns and automatically understands your specific seasonal changes, deployment windows, and user behavior.
-> Real AI for observability - purpose-built intelligence that actually understands how modern distributed systems work.
-> Works as a plug-in layer of intelligence, enhancing any existing observability stack with precise AI insights and no rip-and-replace.
What's Broken with Traditional Observability
Current tools are
Glorified Dashboards:
-> Endless false positives because AI doesn't understand your architecture or service relationships.
-> Requires weeks of manual rule configuration, constantly breaks with every service deployment or architecture change.
-> Analyzes data in isolation: metrics, logs, traces processed by separate disconnected AI models.
-> Alerts after problems hit customers reactive AI that only detects existing failures.
-> Floods teams with uncorrelated alerts from fragmented AI analyzing different data silos.
-> Manual, slow, error-prone root cause investigations that require jumping across dashboards.
-> No understanding of relationships. It can't see how services connect or how failures cascade.
-> Generic seasonal patterns, it struggles with your unique business rhythms and traffic variations.
-> AI as marketing checkbox - generic machine learning that creates more work than it saves.
-> Existing AIOps tools provide shallow correlations, poor accuracy, and require full platform adoption.
The Paradigm Shift: From Static Tools to Intelligent Systems
Outstanding Propositions
for Your Business
Marketing department
Headquarters
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