AI Analysis Engine
Bring your own AI model. SignalManager uses AI to score severity, correlate signals across sources, and suggest fixes automatically.
Model Agnostic
Use any LLM provider or run models on your own infrastructure. No vendor lock-in.
OpenAI
GPT-4o, GPT-4, and future models via API key.
Anthropic
Claude models for nuanced reasoning and analysis.
Ollama
Run local models on your infrastructure. Data never leaves your network.
vLLM
High-throughput self-hosted inference for production workloads.
Severity Scoring
AI evaluates each signal against your codebase context, historical patterns, and impact radius to assign an accurate severity score.
- ✓ Context-aware scoring (not just keyword matching)
- ✓ Configurable severity thresholds
- ✓ Historical trend analysis
Cross-Source Correlation
A Sentry error, a Datadog spike, and a PagerDuty alert may all describe the same incident. AI connects the dots automatically.
- ✓ Temporal and semantic matching
- ✓ Service dependency mapping
- ✓ Incident grouping across tools
Intelligent Fix Suggestions
AI doesn't just identify problems — it proposes solutions with remediation steps, code snippets, and linked documentation.
Root Cause Analysis — Traces the signal back to the most likely cause using stack traces and service topology.
Remediation Steps — Step-by-step instructions tailored to your stack, included directly in generated tickets.
Confidence Scores — Each suggestion includes a confidence rating so your team knows when to trust and when to verify.
For Managers
AI-assigned severity scores mean your team stops debating priority in standup and starts working. Confidence scores help EMs decide when to trust automation and when to have a human verify.
Supercharge Your Signal Analysis
Connect your preferred AI model and let SignalManager turn noisy signals into actionable insights.