Everything You Need to Tame Signal Noise

The full pipeline: ingest signals from any source, analyze with AI, correlate across tools, and generate actionable tickets — all from a single platform. Your developers get context. Your managers get visibility.

Signal Pipeline

Ingest from any source via webhooks, polling, or SDK. Normalize every signal into a unified schema so nothing gets lost and everything is comparable.

“Your PM asks ‘are we ingesting Datadog alerts yet?’ You point them to the dashboard — all connected, all flowing.”

  • Webhooks, polling, and SDK ingestion
  • Unified schema normalization
  • Deduplication and batching
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AI Analysis Engine

BYO AI model. Severity scoring, correlation detection, and fix suggestions powered by your choice of provider. Works with OpenAI, Anthropic, or Ollama.

“Instead of debating severity in standup, the team looks at AI-assigned scores and works down the list.”

  • Severity scoring and prioritization
  • AI-generated fix suggestions
  • OpenAI, Anthropic, Ollama support
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Cross-Source Correlation

Link related signals across Sentry, Datadog, GitHub, and more. Temporal and semantic matching surfaces connections that manual review would miss.

“A Sentry error, a Datadog spike, and a GitHub deploy — all connected into one incident. No manual investigation.”

  • Temporal pattern matching
  • Semantic similarity detection
  • Sentry, Datadog, GitHub, and more

Ticket Generation

Auto-create tickets in Jira, Linear, or GitHub Issues with full context and AI-generated remediation steps. No more copy-pasting between tools.

“Monday morning, the sprint backlog already has prioritized tickets from weekend signals. No one spent time writing them.”

  • Jira, Linear, GitHub Issues
  • Full signal context included
  • AI-generated remediation steps
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Connector SDK

Build custom connectors in TypeScript. Hot-reload during development, built-in testing harness, and type-safe schemas for every signal source.

“Your team built a custom connector for your internal alerting system in an afternoon. Signals flow alongside Sentry and Datadog.”

  • TypeScript-first development
  • Hot-reload and built-in testing
  • Type-safe signal schemas
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Rules Engine

YAML-based routing rules, severity overrides, and auto-assignment. Version-controlled so every change is tracked and reversible.

“P1 payment errors go to on-call. P3 staging noise is suppressed. Your PM configured the routing rules without writing code.”

  • YAML-based routing configuration
  • Severity overrides and auto-assignment
  • Git-friendly version control
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Built on PostgreSQL + Smart SQL

No vector database required. SignalManager AI uses PostgreSQL with smart SQL queries and AI to correlate signals, detect patterns, and surface insights -- without the operational overhead of specialized infrastructure.

Your data stays in a single, well-understood database. Backups, replication, and monitoring work exactly the way your team already knows. AI does the heavy lifting at query time, not at storage time.

  • Single PostgreSQL database -- no vector DB needed
  • AI-powered correlation at query time
  • Standard backup, replication, and monitoring
  • No specialized infrastructure to manage

How It Works

1
Signals stored in PostgreSQL
2
Smart SQL queries find candidates
3
AI analyzes and correlates matches
4
Actionable insights returned

Ready to Tame the Noise?

Start ingesting signals in minutes. Self-hostable and free to get started.