Enterprise data ingestion & ETL automation
Raptor Pipeline
Feed the suite reliably — ingest, clean, transform, classify and deliver data across cloud and on-prem, replacing fragile scripts with production-grade pipelines.
The problem
What it addresses
- Security and risk data arrives from many tools in inconsistent shapes and cadences.
- Fragile scripts and manual workflows break quietly and are hard to trust.
- Without clean, current data, classification and dashboards drift out of date.
Capabilities
What it does
- Ingest, clean, transform, classify and deliver data across cloud and on-premise environments.
- A structured, production-ready data-engineering framework in place of ad-hoc scripts.
- End-to-end observability over mission-critical data workflows.
- Accelerated onboarding of new data sources.
- Data-quality checks so downstream products work from reliable inputs.
Differentiators
Why it's different
- Purpose-built to feed the Raptor suite — classification, controls and dashboards stay current.
- Replaces brittle scripting with a repeatable, observable framework.
- Built for modern data teams and mission-critical workflows.
- Protects existing investments by ingesting from the tools you already run.
In practice
Vulnerability, cloud-config and ticketing data land through governed pipelines that normalise them, so Raptor Board reflects the real, current picture and Raptor Bucket tiers stay accurate.
Where it fits
A platform enabler across the suite
Raptor Pipeline sits alongside the five-stage lifecycle, supporting every stage rather than owning one.
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