Collection and normalisation
Native and external sources, Singularity Marketplace integrations and OCSF normalisation.
Where the module helps during an attack
SIEM does not block attacks itself. It connects evidence across sources, primarily supporting investigation and historical analysis.
| Area | Level |
|---|---|
| Reconnaissance | additional protection |
| Initial access | additional protection |
| Execution and persistence | context |
| Escalation and lateral movement | additional protection |
| Impact | context |
| Investigation and recovery | primary role |
Security data from across your organisation in one place
Singularity AI SIEM is a cloud SIEM built on Singularity Data Lake. It collects telemetry from SentinelOne modules and third-party tools, including firewalls, email, SaaS applications and identity providers, for detection, investigation and response.
Incoming data is normalised to the open OCSF schema. Singularity Data Pipelines, formerly Observo, can enrich, filter and route data before storage, providing a consistent format for cross-source queries.
Storage
Continuously accessible storage without a separate cold archive. Retention depends on the selected plan.
Detection and investigation
Detection rules, threat hunting and Purple AI across the same data.
Response
Singularity Hyperautomation triggers console actions using approved workflows.
How AI SIEM supports investigations
AI SIEM combines endpoint alerts with VPN, firewall and identity provider logs. In one place, analysts can see where a user logged in, what a device contacted and what happened before the alert.
The vendor separates storage from compute and licenses by average monthly ingested data volume. Estimating volume is therefore an early step in each proposal.
- Correlation of endpoint, cloud, identity and network events.
- Historical searches without archive restoration.
- Response with investigation context and less need for a separate SOAR tool.
Who benefits from a central SIEM
AI SIEM suits organisations facing SIEM cost, speed or complexity issues, as well as those building central security event records for the first time. It also helps teams working across multiple consoles.
- Logs are scattered across tools and take too long to connect.
- Historical searches are slow or require archive restoration.
- You need evidence for investigations and internal or regulatory event logging requirements.
Deployment and operation with APPSEC
SIEM value grows with source quality, not source count. We start with the sources most useful for investigation: identities, VPN and remote access, firewalls, email and key servers. Other sources follow according to value and data volume.
Source inventory
Which systems produce logs, their formats and volumes, and which sources matter for detection.
Design
Source priorities, estimated data volume, retention and any migration from an existing SIEM.
Pilot
Integration of selected sources and verification of data processing, initial detections and searches.
Operation
Gradual expansion, administrator handover and support as agreed. Alert assessment needs a clearly assigned owner.
What to check before buying
- Estimated monthly data volume and expected growth.
- Required retention and data location.
- Connectors for key sources and any custom format processing.
- Migration of existing rules and reports from another SIEM.
- Who assesses alerts during and outside working hours.
- Roles, data access permissions and audit records of data use.
