Real time detection and deep historical investigation from the same data, in the same engine, without moving anything between tiers.
Detection
Correlate as it arrives
Logs, alerts, identities, endpoint and network telemetry indexed on arrival and correlated together rather than in separate tools.
Parallel ingest means volume spikes do not queue behind a single entry point, so detection does not degrade under load.
Threat hunting
Hunt across years, not weeks
Ask a question of the whole history and get an answer in seconds, because query cost follows the answers returned rather than the volume stored.
Test a hypothesis against every source at once instead of running it tool by tool.
Incident response
Reconstruct the whole picture
Follow an indicator through infrastructure, identities, devices and sessions to establish what happened and how far it reached.
Timeline, graph and geospatial views come from one index, so the account of events is consistent.
Attribution
Link campaigns over time
Connect malware, infrastructure, tooling and behaviour across incidents that were previously handled as separate cases.
Shared infrastructure and repeated tradecraft become visible once the history is all in one place.
Insider risk
Behaviour, access and association
Correlate personnel, access and activity data over long periods, where the signal is a pattern rather than an event.
Fine grained access control inside the engine, so sensitive investigations stay compartmented.
AI and automation
Context worth giving a model
Selective, connected context for detection models and agentic workflows, rather than bulk retrieval of everything vaguely related.
Provenance preserved, so an automated conclusion can be traced back to the evidence behind it.