Gurucul, a global leader in security analytics, has unveiled its AI Insider Risk Management (AI-IRM) platform, promising a radical rethink of how organizations detect and respond to insider threats. Combining behavioral analytics, identity intelligence, and AI-powered automation, AI-IRM positions itself as the first native AI Insider Analyst, streamlining workflows and bolstering defense against both human and non-human threats.
The launch comes at a time when insider risks are surging. According to the 2024 Insider Threat Report by Cybersecurity Insiders, 83% of organizations reported at least one insider attack in the past year, ranging from malicious employees to AI agents and third-party accounts. Traditional security tools often leave gaps, with siloed alerts and slow remediation processes. Gurucul claims AI-IRM addresses these shortcomings with a unified, automated approach.
“Gurucul empowers Insider Risk Management teams to move beyond fragmented point products,” said CEO Saryu Nayyar. “Our AI-Insider Analyst transforms detection and response workflows, automating alert triage and response while keeping humans in the loop. This allows analysts to focus on high-risk investigations and rapid remediation.”
Key Capabilities and Benefits
- Risk Reduction & Coverage: AI-IRM minimizes identity and access risks, providing comprehensive detection across human users, service accounts, AI agents, and state-sponsored threats.
- Accelerated Triage & Response: AI-powered triage and alert enrichment reduce analyst workload by up to 83%, enabling faster, bias-free decision-making.
- Real-Time Data Protection: Intelligent DLP with automated response playbooks blocks data exfiltration across endpoints, cloud, print, and email.
- Day 0 Threat Protection: Prebuilt dashboards, models, and detection templates provide immediate coverage upon deployment.
- Compliance & Privacy: Granular RBAC, data masking, and adherence to GDPR, HIPAA, PCI DSS, and NIST ensure regulatory alignment.
AI-IRM integrates multiple disciplines—User and Entity Behavior Analytics (UEBA), identity and access analytics, and automated response (SOAR)—into a single platform. It also leverages a built-in AI Analyst and SME AI Copilot, trained on historical insider threat cases, to accelerate investigations with context-rich narratives and actionable insights.
Nilesh Dherange, CTO of Gurucul, emphasized the importance of transparency and human oversight: “Much like humans, AI can develop biases over time. Our system continuously trains on historical cases and human validation to ensure trusted, accurate risk scoring.”
Additional features include flexible data ingestion, contextual natural language threat hunting, custom use case development, agentless deployment options, location trust services, and integration with any data lake or cloud environment, including Snowflake, Databricks, AWS, GCP, and Azure.
With AI-IRM, Gurucul claims organizations can reduce insider risk by over 50%, detect threats across all insider types, and stop data loss in real time, all while maintaining compliance and operational transparency.
In a landscape where hybrid workforces and complex IT environments make insider risk ever more challenging, Gurucul’s AI-IRM aims to set a new standard for proactive, AI-driven threat management.
Power Tomorrow’s Intelligence — Build It with TechEdgeAI
