Signal Pipeline
Ingest signals from any source via MCP server, REST API, webhooks, or the Connector SDK. Normalize everything into a unified schema for AI analysis.
Flexible Ingestion Methods
Connect any signal source using the method that fits your infrastructure.
MCP Server
Built-in MCP server for direct AI client connectivity. Connect from Claude Desktop or any MCP-compatible client.
REST API
Full REST API for programmatic ingestion, automation scripts, and CI/CD pipelines.
Webhooks
Receive push-based signals in real time. Supports HMAC verification, retry logic, and batched payloads.
Connector SDK
Build custom connectors in TypeScript for any source. Full type safety with hot-reload.
Unified Normalization
Every signal is transformed into a consistent schema so AI models can analyze across sources.
Unified Schema — Raw payloads are mapped to a standard envelope with source, timestamp, severity hint, and payload fields.
Metadata Extraction — Stack traces, CVE identifiers, affected endpoints, and service names are automatically parsed.
Schema Validation — Malformed signals are quarantined with detailed error reports for debugging.
Deduplication & Grouping
Duplicate signals are automatically detected and grouped. A single Sentry error firing 200 times becomes one enriched signal, not 200 tickets.
- ✓ Content-hash based dedup
- ✓ Configurable time windows
- ✓ Cross-source grouping
Real-time Processing
Signals flow through the pipeline in seconds, not minutes. Stream processing ensures your team is alerted before issues escalate.
- ✓ Sub-second ingestion
- ✓ Backpressure handling
- ✓ Pipeline health dashboard
For Managers
The pipeline health dashboard shows you at a glance whether signals are flowing from all connected tools. You will know immediately if a connector goes silent — before your team does.
Related Features
Get Early Access to Signal Pipeline
Join the waitlist to be first in line. Connect webhooks, configure polling, or build a custom connector on day one.