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Imperum
AI-Driven Autonomous SOC
Reduce 90% of manual SOC workload with AI-driven security operations powered by Imperum.
A hyperautomated platform unifying Ingestion, Detection and Response, powered by Forensic Analysis & Investigation
Traditional SOCs Are Built for a Threat Landscape That No Longer Exists
The average enterprise SOC receives over 10,000 alerts per day. Analysts can meaningfully investigate 20-30. The rest? Ignored, deprioritized, auto-closed. Somewhere in that mountain is the alert that becomes a breach.
SIEM promised to solve this. SOAR tried to automate parts. Neither went far enough. What’s needed isn’t incremental improvement, it’s a fundamental rethink.
Hyperautomation:
Beyond SIEM. Beyond SOAR.
- Automated Alert Triage: Every alert is automatically enriched with context, correlated against threat intelligence, and scored for severity, before a human ever sees it.
- Autonomous Detection & Response: For known threat patterns, Imperum acts immediately. Isolating endpoints, blocking IPs, quarantining files at machine speed, with full audit trails.
- Unified Security Operations: Integrates across your entire stack, SIEM, EDR, DLP, PAM, firewall, cloud creating a single pane of glass. No more swivel-chair analysis.
- AI-Driven Threat Intelligence: Continuously ingesting global and India-specific threat feeds. Detections are current, relevant, and tuned to your industry and geography.
- Compliance Automation: Regulatory reporting that took days now takes minutes. Automatically maps events to DPDP, SEBI CSCRF, ISO 27001, PCI-DSS.
We Don’t Just Deploy Imperum. We Operationalise It.
We’ve spent years deeply customizing Imperum tuning detection logic, building industry-specific playbooks, integrating it into our Managed SOC, training our analysts to leverage every capability. When you get Imperum through AiCyberWatch, you get a battle-tested engine backed by a team that lives inside it every day.
Imperum vs What You’re Probably Evaluating
vs. Standalone SIEM (Splunk, QRadar, Elastic)
- A SIEM: collects and correlates. Imperum does that plus automated triage, investigation, and response. It’s the automation layer that makes your SIEM actually useful.
vs. SOAR Platforms (Palo Alto XSOAR, Swimlane)
- SOAR promised : automation but delivered complexity. Most deployments need dedicated engineers to maintain playbooks. Imperum’s playbooks are built, tested, and refined by the same analysts who use them daily. No SOAR team required.
vs. XDR Platforms (CrowdStrike Falcon, Palo Alto Cortex)
- XDR excels : XDR excels within one vendor’s ecosystem. Real environments are multi-vendor. Imperum integrates across your entire stack regardless of vendor. No lock-in. No blind spots.
Autonomous SOC vs Traditional SOC: Why AI-Driven Security Operations Are Replacing Legacy SOC Models
Below is a well-organized table summarizing the information about Autonomous SOC vs Traditional SOC
| Capability | Traditional SOC | Autonomous SOC (AI-Driven SecOps) |
|---|---|---|
| Alert Handling | – Manual triage of thousands of alerts daily | – AI filters, correlates, and prioritizes alerts automatically |
| Threat Detection | – Rule-based detection (SIEM dependent) | – Behavioral analytics + AI anomaly detection |
| Response Time (MTTR) | – Minutes to hours | – Seconds to minutes (automated response) |
| Analyst Workload | – Extremely high (alert fatigue) | – Reduced by up to 80–90% via automation |
| False Positives | – High volume | – Significantly reduced using AI correlation |
| Threat Investigation | – Manual, time-consuming | – Automated root-cause analysis |
| Scalability | – Requires hiring more analysts | – Scales instantly with automation |
| 24/7 Coverage | – Expensive, resource-heavy | – Always-on autonomous monitoring |
| Cost Efficiency | – High operational cost (people-heavy) | – Lower cost via automation + efficiency |
| Consistency | – Human-dependent | – Standardized, repeatable AI workflows |
| Threat Hunting | – Limited, reactive | – Continuous, proactive AI-driven hunting |
| Integration | – Complex and slow | – API-driven, fast integrations (SOAR, EDR, etc.) |
By The Numbers
How AiCyberWatch Works
- Ingest : Collect and normalize data from any source (cloud, on-prem, endpoints, network).
- Detect : Apply AI models to identify threats in real-time with high accuracy.
- Respond : Automate containment and remediation with customizable playbooks.
- Investigate : Conduct deep forensic analysis with automated evidence collection and correlation.
- Optimize : Continuously improve with machine learning and threat intelligence updates.
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