BigID Launches AgentIQ for Autonomous Data Security Operations

Prompt-driven data security arrives

BigID has introduced AgentIQ, an agentic automation layer that allows enterprises to run data security and compliance operations through natural language prompts. The platform works within BigID's existing interface or directly through Claude, Copilot, GPT, and Gemini, eliminating the need for dedicated security analysts to execute routine queries and remediation tasks.

According to details first reported by PRNewswire, the system handles complete workflows from a single request—identifying risks, prioritizing them by business context, executing fixes, and logging all actions for audit trails.

How the automation works

AgentIQ processes requests that span the full security lifecycle. A user can prompt the system to "find sensitive data exposed to the internet, rank it by business risk, and revoke public access on the top ten." The agent identifies exposure across connected systems, applies risk scoring, remediates approved items, and documents every step.

The platform addresses AI-specific compliance challenges as well. When asked which AI systems access regulated data or violate policy, AgentIQ maps data flows to both sanctioned and shadow AI deployments, flagging violations before external audits surface them.

Other supported workflows include identifying and revoking excessive access permissions, fulfilling data subject requests across multiple systems, and investigating security incidents to determine scope and impact.

Three deployment models

BigID offers three paths for implementing AgentIQ. Enterprises can purchase pre-built agents that deploy immediately, build custom agents on the AgentIQ platform tailored to internal workflows, or integrate existing agents from third-party AI platforms through BigID's Model Context Protocol (MCP) implementation.

The platform spans BigID's 200-plus integrations covering on-premises systems, cloud infrastructure, SaaS applications, databases, and file storage. This breadth allows agents to operate across an organization's entire data landscape without requiring consolidation or migration.

Security and governance controls

AgentIQ enforces permissions at the API and MCP layer rather than relying on system prompts. Agents inherit the requesting user's access rights, ensuring that automation cannot exceed human authorization levels. Every action is logged with attribution to a specific person, creating accountability chains for compliance documentation.

Enterprise security features include password vaulting, bring-your-own-key encryption, telemetry monitoring, and air-gap deployment support. The architecture avoids vendor lock-in by supporting multiple models and agent frameworks rather than requiring commitment to a single AI provider.

Why it matters

Data security teams face a persistent resource constraint: the number of analysts available to investigate alerts, respond to incidents, and maintain compliance controls. AgentIQ addresses this bottleneck by automating the full remediation cycle, not just detection. The platform's ability to work within existing AI interfaces—rather than requiring adoption of yet another security console—reduces friction for organizations already standardized on enterprise AI tools. For compliance-heavy industries, the combination of autonomous operation with granular audit trails may prove particularly valuable as regulatory scrutiny of AI systems intensifies.

Dimitri Sirota, CEO and co-founder of BigID, emphasized that effective agents require deep data context to avoid confident but incorrect responses about sensitive information. Nimrod Vax, head of product and co-founder, noted that customers specifically requested avoiding both additional consoles and dependence on a single AI model.

BigID announced the AgentIQ launch on September 21, 2026, with details first reported by PRNewswire.