Gurucul Unveils Industry's First AI-Powered Insider Risk Management Platform with Native Convergence and Agentic AI for Autonomous Threat Detection and Response

Revolutionizes Insider Threat Defense with Integrated AI-Powered UEBA, Identity Analytics, Intelligent DLP, External Risk Indicators and AI-Analyst

LOS ANGELES, Sept. 17, 2025 /PRNewswire/ -- Gurucul, a global leader in security analytics and risk management, today announced the launch of its AI Insider Risk Management (AI-IRM) product. This ushers in a new era of unified insider threat defense, extending its award-winning insider threat solution to the industry's first native AI Insider Analyst. Extending autonomous triage, bias-free risk scoring, context-rich investigation, and human and AI collaboration, AI-IRM automates response workflows directly into insider risk management operations.

Organizations face an unprecedented rise in insider threats, from employees, contractors and third parties to non-human accounts and AI agents. According to Cybersecurity Insiders' 2024 Insider Threat Report, 83% of organizations reported at least one insider attack in the past year.

Until now, teams struggled with siloed tools, noisy alerts, resource constraints and process bottlenecks that slowed remediation. Gurucul AI-IRM addresses these challenges by combining advanced User and Entity Behavior Analytics (UEBA), identity and access analytics (IdA), intelligent data loss prevention (DLP), and native automated response (SOAR).

"Gurucul empowers Insider Risk Management teams to move beyond fragmented point products with natively converged behavioral and identity-centric analytics, smart data protection, policy enforcement, and agentic AI that proactively surfaces and prevents real insider threats," said Saryu Nayyar, CEO, Gurucul. "Our AI-Insider Analyst transforms the insider threat detection and response workflows by automating alert triage and response with human collaboration. This enables organizations to leverage our expansive use case library, enabling Day 0 coverage so the existing analyst team can focus on the high-risk investigations and response actions."

By shrinking blind spots, Gurucul is enabling organizations to:

• Reduce Insider Risk by Over 50%: Minimizes the identity and access threat surface using AI-powered UEBA, Identity Analytics, and Privileged Access Intelligence.
• Detect Every Insider Risk: Advanced behavioral models, peer baselining, and holistic context unify all sources—users, service accounts, identities, locations, endpoints, and cloud telemetry— and provide comprehensive coverage across human insiders, non-human identities, AI agents as digital employees, and state-sponsored threats.
• Accelerate Triage and Remediation: AI-Insider Analyst and Sme AI Copilot augment every step of the workflow, driving instant triage, bias-free risk scoring, automatic alert enrichment, and reductions of up to 83% in analyst time.
• Stop Data Loss in Real Time: Intelligent DLP with bi-directional egress integrations automates sensitive data discovery and prevents exfiltration, with SOAR-integrated playbooks that instantly isolate risky users, revoke access, and block unsanctioned activity across email, endpoints, print, and cloud channels.
• Accelerate with Day 0 Insider Threat Protection: Out-of-the-box pipelines, models, dashboards, and customizable detection templates speed up deployment and ROI.
• Ensure Compliance and Privacy: Granular RBAC, data masking, and regulatory alignment with GDPR, NIST 2, HIPAA, PCI DSS, and CISA.

"Much like humans, AI can develop biases over time. Creating a system that is transparent and can be trusted is non-negotiable," said Nilesh Dherange, CTO, Gurucul. "The benefit of a native AI-Insider Analyst is the cohesion it has, with 10+ years in developing insider risk machine learning detections. It's trained on contextualized data and is continuously trained from historical cases, feedback and keeping a human-in-the-loop to validation process."

AI-IRM key capabilities include:

• Comprehensive Insider Threat Content: Prebuilt pipelines, dashboards, detection models, watchlists, playbooks, risk indicators, and reports to accelerate deployment and threat coverage.
• Expansive Use Case Coverage: Comprehensive coverage across human users, non-human identities, AI agents, and state-sponsored threats with hundreds of out-of-the-box use cases and thousands of ML-driven detections.
• AI Analyst & Sme AI Copilot: AI-powered alert triage and response trained on insider threat investigations empower faster, more accurate responses with automated incident narrative.
• Flexible Data Ingestion: Ingests non-standard and enrichment data sources with ease, including federated search for data not ingested in the platform.
• Identity and Access Analytics: Proactively reduces the identity threat surface and enforces Zero Trust principles.
• Advanced UEBA and Contextual UAM: Self-learning behavioral analytics are combined with user activity monitoring and a 360° timeline view for deep context.
• Powerful Contextual Natural Language Search and Threat Hunting: Blazing-fast AI-powered natural language search, federated queries, retrospective analysis and replay.
• Custom Use Case Development: Behavior-based templates and a built-in STUDIO that empowers analysts to build detections tailored to organizational risk.
• Risk-Driven Detection and Prioritization: A flexible enterprise risk engine supports human risk scoring, patented risk aggregation, and early warning models.
• Comprehensive DLP Coverage: Intelligent, AI-based DLP across all egress channels with cross-channel exfiltration detection and protection leveraging bidirectional integrations with other enterprise security solutions.
• Privacy and Compliance: Built-in granular RBAC, data masking, and user-level monitoring ensure alignment with regional privacy laws and global regulatory mandates (GDPR, NIST 2, HIPAA, PCI DSS, CISA).
• Automated Response: Includes out-of-the-box insider threat response playbooks, third-party SOAR integrations, robust case management, and groundbreaking AI-Insider Analyst.
• Agentless Architecture with Optional Endpoint Agent: Enables lightweight deployment with enhanced monitoring and sensitive data discovery as needed.
• Location Trust Service: Non-IP-based device location detection for precise identification of unauthorized access attempts.
• Global Threat Intelligence Alignment: Backed by research partnerships, threat intel feeds, and alignment with industry frameworks and compliance standards.
• Your Data Lake and Cloud: Only product that provides comprehensive Insider Risk coverage on any data lake (Snowflake, Databricks, Amazon S3 etc.) and any cloud (AWS, GCP, Azure, etc.), enabling enterprises to own their data and deployment strategy.

With the launch of AI-IRM, Gurucul sets a new standard for Insider Risk Management. Delivering the industry's first truly AI-powered solution that converges behavioral analytics, identity intelligence, data protection, adaptive detections and response automation. Built for modern threats, hybrid workforces, and complex IT environments. Gurucul empowers organizations to proactively detect, prioritize, and contain insider threats at scale—with speed, precision, and transparency.

About Gurucul
Gurucul is a unified data and security analytics company founded in data science that delivers radical clarity about insider and cyber risk. We analyze enterprise data at scale using machine learning, comprehensive threat content and secure artificial intelligence. Instead of useless alerts, you get real-time, actionable information about high-risk threats with automated response options. Our cloud-native platform is open and flexible enabling you to own your data. Deploy it anywhere, use any data lake, and integrate it with any security tool. To learn more, visit gurucul.com and follow us on LinkedIn.

For more information, visit www.gurucul.com/AI-IRM

PR contact:

Shannon Van Every
Force4 Technology Communications
[email protected]

SOURCE Gurucul