Connect the Dots In AI & Data

Identify and categorize sensitive data across structured, semi-structured, and unstructured sources with patented, AI-driven precision.

Discover, assess, and take action on data & AI risk across every cloud, SaaS, and on-prem environment – at enterprise scale.

Automate and orchestrate remediation flows with masking, redaction, labeling, permissions, and retention enforcement.

Gain full visibility and control into who accesses what data – monitor activity, enforce least privilege, and prevent breaches.

Label data by type, sensitivity, and AI readiness with automated, identity-aware tagging for policy enforcement and governance accuracy.

Protect sensitive data in motion and at rest through dynamic masking and redaction.

Identify and delete redundant, obsolete, or trivial data to reduce risk and storage cost across all environments.

Continuously map, measure, and enforce compliance controls across data, AI, and regulatory frameworks.

Detect, prevent, and remediate data leaks – no agency, no latency, full SaaS.

Find and flag data that moves across regions or jurisdictions to reduce compliance and sovereignty risk.

Expose shadow AI and unsanctioned copilots. Detect unauthorized use, assess vendor risk, and surface AI resources exposing sensitive data.

Track and control employee AI interactions. Label data for AI use. Apply guardrails. Intercept and manage prompts. Enforce user and role-based data access rights.

Understand your AI risk posture with AI SPM. Detect vulnerabilities in models and agents, control AI access, and Identify when sensitive data is used in AI.

Discover and prepare data for AI training. Detect and cleanse sensitive fields. Apply compliance controls. Continuously monitor data across vector databases.

Evaluate AI risk posture. Manage AI security controls and prompt protection. Detect vulnerabilities and anomalous access patterns. Enforce policies for compliant, transparent AI use.

Detect when AI agents access sensitive data. Enforce permissions, monitor behavior, and flag unusual agentic activity before it leads to exposure.

Track, assess, and prioritize regulatory and control risks across data and AI environments.

Monitor compliance status, generate reports, and automate remediation for violations.

Evaluate privacy and AI risks with continuous monitoring and actionable insights.

Visualize how personal and sensitive data flows across systems, regions, and AI pipelines.

Centralize and enforce consent preferences for data and AI use across all channels.

Give users control over how their data and AI interactions are used and processed.

Automate DSAR, deletion, and portability workflows with full audit trails and compliance assurance.

Simplify cookie consent and tracking compliance across websites and mobile apps.

Monitor, assess, and govern vendor data and AI sharing to reduce third-party risk.

Automatically classify files, emails, chats, and code at scale using advanced machine learning and AI classification models.

Categorize and label structured and unstructured data by business, domain, or semantic meaning to streamline governance.

Build the first catalog purpose-built for unstructured genAI data with semantic search and curation for RAG and model training.

Enrich metadata with AI-driven inference for ownership, domain, and lineage to deliver a complete governance view.

Leverage BigID’s Agent for Stewardship to automate data curation, validation, and enrichment at scale.

Label data by sensitivity, taxonomy, or business context across buckets, folders, tables, and vector databases.

Mask or redact sensitive data before use in RAG or model training, and validate compliance with AI and privacy regulations.

Simplify testing and reporting for emerging AI frameworks like the EU AI Act and NIST AI RMF.

Track and restrict access to genAI data by user, model, or agent to maintain security and accountability.