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The LLM identifies the user's intent and orchestrates tool calls to perform anomaly detection and causal analysis.
The LLM invokes tools to complete anomaly detection and causality identification.
Using eBPF data, the LLM removes misleading causal relationships to refine the analysis
Conduct a holistic analysis of Traces, Logs, and Metrics for each suspect node to reach a defensible finding.
Following the integrated suspect-node analysis, re-validate with eBPF telemetry to produce the final root-cause (RCA) report, substantiated by trace, log, and metric evidence.
Why you need Syncause ?
It's not a lack of data — it's the lack of insight.
AI accelerates deployment but removes human context. Failures in AI-generated microservices leave engineers guessing at logic and data flows.
Critical service failures in AI-generated modules with opaque business logic
Turnover and undocumented legacy code leave black boxes that complicate troubleshooting.
Performance issues in "black box" business logic after personnel turnover
Traces confuse, logs lack context, metrics lack causality — legacy tools can't keep up with modern complexity.
Multiple alerts trigger simultaneously, unable to quickly determine root cause
Experience instant fault diagnosis — no signup needed.