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Universal Log Lake
Native ingest for syslog, Windows events, AWS/Azure/GCP audit, EDR, and NetFlow. Hot for 90 days, cold-but-queryable for 7 years.
Solutions · CybersecurityGENEDATA / 01
Connect the signals.Focus the response.
Bring security telemetry into one analytical context. Follow threats across sources and retain the evidence behind each investigation.
Shared context · Lineage · Governance
Connected
Your sources
Endpoint signals
Network events
Cloud audit logs
Connected intelligenceThreat analytics
Governance
Business impactInvestigation & response
Shared contextLineageGovernance
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Hunt Across Years
Run YARA-style and behavioral queries across petabytes of historical events in seconds — without rehydrating cold storage.
03
Detection-as-Code
Author Sigma and KQL detections, version them in Git, deploy through CI — with built-in MITRE ATT&CK mapping and back-test tooling.
Built On
The products behind this solution.
A SOC needs volume at low cost, fast retrospective search, and automation that does not create a new privilege hole.
GeneFlow
Ingests syslog, EDR, NetFlow, and cloud audit at 10M+ events/sec, landing them in open format you own rather than a vendor's index.
Learn moreGeneCatalog
Classifies and governs the log lake itself, so security telemetry containing PII is handled under the same policy as everything else.
Learn moreCortex SQL
Runs hunt queries across years of history in seconds without rehydrating cold storage or paying per-ingest licensing.
Learn moreCortex AI
Triages alerts, correlates across signal types, and drafts detections — under the analyst's own permissions, not a service account.
Learn moreBehavioural Detection
The signal that matters is deviation, not volume.
Signature detection catches what you already know about. Behavioural baselining catches the account that is doing something it has never done before — an authentication pattern, an egress volume, a query shape that sits outside its own learned history.
How the SOC Uses It
Ingest, detect, hunt, respond.
The same store serves real-time detection and multi-year retrospective hunting, so an investigation never stops at the edge of the hot window.
Ingest everything
Syslog, Windows events, cloud audit, EDR, and NetFlow land in one governed store rather than being sampled to control licence cost.
Detect as code
Sigma and KQL detections live in Git, deploy through CI, and are back-tested against historical telemetry before going live.
Hunt across years
Query petabytes of cold telemetry directly, without a rehydration job, so scoping questions get answered the same day.
Respond with context
Alerts arrive enriched with asset, identity, and prior-incident context, and agentic triage drafts the initial assessment.
SOC Capabilities
What your analysts actually get.
Most SIEM pain is licence-driven sampling and slow cold-storage access. Both are design targets here.
No ingest-based sampling
Cost scales with compute rather than ingest volume, so there is no incentive to drop the log source you will later need.
MITRE ATT&CK mapping
Detections carry technique mappings, so coverage gaps are visible as a matrix rather than discovered during an incident.
Seven-year hunt window
Cold telemetry stays directly queryable, so a newly disclosed indicator can be checked against years of history immediately.
UEBA baselining
Per-identity and per-asset behavioural baselines catch credential misuse that no static rule was written for.
Detection back-testing
Evaluate a new rule against historical data before deployment to see its true-positive and noise profile in advance.
Agentic triage
First-pass alert assessment drafted automatically with supporting evidence, leaving analysts to adjudicate rather than gather.
Who Benefits
Across the security organisation.
Detection, hunting, and compliance reporting usually run on three different systems. Here they run on one.
SOC Analyst
Scope an incident in one query
Pivot from an indicator across every log source and back through years of history without waiting on a restore job.
Scoping in minutes rather than days.
Threat Hunter
Test a hypothesis against real history
Run behavioural queries across the full retention window, then promote what works into a versioned detection.
Hunts that graduate into durable coverage.
Security Leadership
Stop paying per gigabyte to see your own logs
Decoupling cost from ingest volume removes the pressure to reduce visibility in order to control the licence bill.
Coverage decisions driven by risk, not licensing.
Versus Legacy SIEM
What changes on a warehouse-native SIEM.
Legacy SIEM pricing makes visibility expensive, which is exactly backwards for a detection problem.
| Dimension | Before Genedata | With Genedata |
|---|---|---|
| Pricing model | Per gigabyte ingested, punishing full coverage | Compute-based, so ingest breadth is not rationed |
| Historical access | Cold data requires a rehydration job | Seven years directly queryable |
| Detection lifecycle | Rules edited in a console, untested | Versioned in Git, back-tested, deployed via CI |
| Coverage visibility | Gaps discovered during an incident | ATT&CK matrix showing coverage continuously |
| Data ownership | Telemetry locked in a vendor's store | Open formats in your own storage |
Streaming + batchIngest Mode
ConfigurableHot Window
7 yearsCold Retention
Flat, hard-cappedIngest pricing
The next step
Detect, hunt, and respond on one engine.
Replace your SIEM, UEBA, and security data lake with a single governed platform. Genedata Cybersecurity gives your SOC team the reach of a data lake with the response speed of a tier-one SIEM — without the vendor lock-in.
FAQ
Cybersecurity, answered.
What SOC leaders and detection engineers ask before replacing a SIEM.
How does this compare to per-ingest SIEM licensing?
Storage and compute are separate and priced separately, so retaining more telemetry does not scale your bill the way per-GB ingest licensing does. That changes what you can afford to keep, which is usually the binding constraint on hunt quality.
Can we hunt across cold data?
Yes, without a rehydration step. Data older than the hot window remains directly queryable in open format, so a hunt across years is a longer query rather than a restore request and a wait.
Is detection-as-code supported?
Detections are authored as code, versioned in Git, and deployed through CI, with MITRE ATT&CK mapping and back-testing against historical telemetry before they go live.
Do AI agents get standing access to security data?
No. Agents run under the invoking analyst's permissions and every action is recorded in the same audit chain as a human query. An agent cannot reach telemetry its operator could not.
Can we keep our existing SOAR and ticketing?
Yes. Alerts route to your existing operational tooling via webhook, PagerDuty, or Slack — this replaces the data layer rather than the response workflow.
Related content
Catalog
Detection Library
MITRE ATT&CK-mapped detections with deployment templates.
RunbookSOC Operational Runbook
Triage, hunt, and incident workflows on the platform.
GuideMigrating Off a Legacy SIEM
Dual-running detections during a phased cutover.
RelatedSecurity
The platform's own zero-trust posture and audit model.
Take the next step
Hunt across your own history.
Bring a real investigation to a working session and run it against years of telemetry.