SIEM01
Reason about attack narratives
Rover correlates activity across identity, cloud, endpoint, application, and audit sources so multi-step attacks are treated as stories, not isolated alerts.
Agentic SIEM
Agentic SIEM
Rover is an Agentic SIEM for machine-speed attacks: adaptive detections turn signals into cases, agents investigate with cited evidence, and fast search runs on S3-hosted indices.
01 Primary
Agentic SIEM
02 Workflow
Agentic SecOps
03 Engine
S3 Search
Agentic SIEM for attacks that move at machine speed.
Rover keeps the SIEM jobs: detection, investigation, audit, and response. The change is architectural: detections produce signals, agents assemble cases, and searchable S3 memory gives every conclusion evidence.
Cases02
Turn signals into cases
Agents group related signals, build timelines, cite source events, score severity, and produce a case an analyst can accept or challenge.
Detection03
Adapt detections to your environment
Generic rules are only the starting point. Rover learns entities, baselines, assets, and source coverage so detections reflect your operating reality.
S3 Search04
Keep searchable memory in S3
Searchable indices live in S3, so agents can validate cases against retained telemetry without forcing every byte into the SIEM hot tier.
Agentic SecOps
From signals to evidence-cited cases.
Rover agents do the repetitive work after detections fire: collect evidence, join sources, test hypotheses, explain confidence, suggest next pivots, and preserve the trail.
InputSignals + detections
SearchS3 indices + raw events
OutputCases, gaps, actions
agent run / impossible-travel
ready
investigate alert.id = "IAM-4812"
scope s3.index.identity, cloud.audit, vpn, edr
goal build case, explain risk, cite evidence, suggest response
guardrail cite source events before action
scope s3.index.identity, cloud.audit, vpn, edr
goal build case, explain risk, cite evidence, suggest response
guardrail cite source events before action
sample workflow
1
Collect evidences3 indices, identity, vpn, cloud, endpoint
waiting
2
Group related signalsuser, device, ip, account, process
waiting
3
Build attack narrativetimeline, severity, confidence, evidence
waiting
4
Recommend detection updateadaptive coverage improvement queued
waiting
Three detection layers on S3-native search.
Rover combines core detections, adaptive environment-specific detections, and behavioral baselines with S3-hosted indices that make retained telemetry searchable for agents and analysts.
Baseline coverage
Start with core detections for common attack behaviors across identity, cloud, endpoint, application, SaaS, and audit sources.
Environment logic
Generate and tune detections around your assets, business units, normal access paths, cloud accounts, and operational patterns.
Learn baselines
Model expected behavior for users, hosts, services, and workloads so agents can reason about activity that does not belong.
Index in S3
Build searchable indices in S3 for entities, time ranges, source metadata, and raw-event pointers across retained telemetry.
Reason with agents
Agents assemble signals into evidence-cited cases, surface gaps, and feed improvements back into detection coverage.
Security coverage should not be priced out of the SIEM.
Legacy SIEM economics force teams to choose which telemetry they can afford to investigate. Rover keeps the SIEM experience while moving searchable memory and indices to S3.
Legacy SIEM pressure
- Hot-tier storage makes long retention expensive.
- Teams drop or sample telemetry that agents need for investigation.
- Static rules create alert volume faster than analysts can investigate.
- AI summaries sit on top of alerts but cannot cheaply validate enough history.
Rover Agentic SIEM
- Agents and analysts search S3-hosted indices with source-level evidence.
- Telemetry stays retained in S3, keeping cost low while preserving investigation depth.
- Adaptive detections and behavioral baselines reduce noise before cases reach analysts.
- Every case leaves a reproducible trail for response, review, and detection improvement.
The Rover difference.
Rover borrows the right lesson from the new detection era: the system has to reason. Rover applies that through an Agentic SIEM with S3-backed search and cost-aware retained telemetry.
Signals become cases
Rover treats alert triage as a SIEM-native workflow that turns related signals into evidence-cited cases.
Analyst-agent workflow
Agents gather evidence and propose decisions; analysts approve response, document cases, and improve detections.
S3-backed investigation
Search runs over S3-hosted indices so older and lower-frequency telemetry remains useful during incidents.
Adaptive coverage
Rover tunes detection logic around your environment so generic rules become operating-context-aware signals.
Reduce SIEM pressure
Move index and retention economics to S3 while keeping the SIEM experience for alerts and response.
Preserve the story
Keep alerts, searches, agent findings, entity pivots, notes, timelines, and exports together.
Early access