Secure Agents for Security Operations
Full Coverage Across Every Source. No Schemas. No Gaps.
Crogl agents deliver autonomous alert triage and AI-powered threat coverage across your entire data environment — SIEMs, data lakes, EDRs, cloud logs, threat intelligence feeds — in their native format. No normalization, coding, or schema expertise required.
Every alert. Full investigation. Complete audit trail.
The Coverage Gap
Your data is everywhere. Your analysts can’t be.
Security data doesn’t live in one place. It’s distributed across SIEMs, data lakes, EDRs, cloud logs, and ticketing systems , each with its own schema, its own query language, its own structure. Getting a complete picture of a threat means querying across all of it.
Today that requires analysts who know every schema, every query language, every data location. That bar is impossible to meet consistently, and the gaps it creates are exactly where threats hide.
Hours
For a thorough cross-lake investigation when analysts must navigate schemas manually
Dozens
Of separate schemas, query languages, and data locations analysts must master
100%
Of threat actors who exploit the gaps between data sources your team can’t easily cross-reference
The Crogl Approach
One investigation. Every data source. No expertise required.
Query Across Everything, Natively
Crogl connects to your full data environment: Splunk, Sentinel, Databricks, Snowflake, S3, CrowdStrike, Cribl. It queries each source in its native format. No normalization pipeline. No schema mapping required before investigations can run.
Knowledge Graph Builds the Full Picture
Every query result feeds into Crogl’s knowledge graph, which assembles a complete, cross-domain picture of the threat. User behavior from the SIEM. Endpoint telemetry from the EDR. Access patterns from the data lake. Threat intelligence from external feeds. All correlated automatically.
Analysts Investigate in Plain Language
Your analysts interact with Crogl in natural language: not SPL, KQL, or SQL. They ask the question. Crogl queries the right sources, assembles the context, and delivers a complete finding. No schema expertise required. No data source left unqueried.
In Production Today
Fortune 500 Financial Institution
Minutes
Cross-lake investigation time
Previously
~1 hour per investigation. Analysts navigating schemas across distributed data lakes manually.
After
Investigations completed in minutes. Analysts query in plain language. No schema knowledge required.
Security data distributed across multiple cloud data lakes, each with different schemas and query requirements. Crogl queries all of them natively, giving analysts complete cross-domain visibility for the first time.
What Crogl Delivers
Native Query Across Every Source
Splunk, Sentinel, Databricks, Snowflake, S3, CrowdStrike, Cribl: queried in their native format. No normalization. No schema mapping. No source left out because it was too complex to integrate.
Threat Intel as a First-Class Input
CRISP reports, ISAC advisories, vendor bulletins. Crogl treats threat intelligence the same way it treats alerts. Every advisory is analyzed, cross-referenced against your environment, and documented.
Natural Language Investigation
Analysts ask questions in plain language. Crogl determines which sources to query, how to query them, and how to assemble the results. No query language expertise required. No schema memorization.
Proactive Threat Hunting
Crogl doesn’t wait for alerts. It proactively hunts for indicators of compromise and adversarial behavior patterns across your full data environment, continuously, at a scale no human team can match.
Query Across Your Full Stack
“Every source. Native format. No normalization required.”
See Your Full Environment Covered
What threats are hiding in the gaps between your data sources?
We’ll show you exactly how Crogl investigates across your full stack: using your data sources, your schemas, your environment.
Deployed across SIEMs, data lakes, EDRs, and cloud environments at Fortune 500 scale.