Bigeye

Enforces policy compliance, user entitlements, and data access permissions for AI agents at runtime.

Capability to find, understand, and reuse approved AI agents across the enterprise to improve AI adoption with confidence.

Runtime enforcement module that ensures AI applications only access trustworthy data by enforcing data access policies at runtime.

Enterprise platform for ensuring data quality, identifying sensitive data, and managing AI governance. Combines data observability with lineage tracking, anomaly detection, sensitive data discovery, and runtime policy enforcement to enable responsible AI scaling.

Automatically detects anomalies in data pipelines to identify quality issues and potential risks.

ML-powered system that identifies data anomalies and quality issues in real-time across data pipelines, accelerating issue detection and resolution.

AI-driven data quality capabilities that improve data accuracy and reliability for AI applications.

Real-time data quality monitoring, classification, and anomaly detection to ensure security and compliance posture before data powers AI decisions.

Aligns business definitions, certifies datasets, manages data ownership, and enforces governance policies across the enterprise.

End-to-end data lineage tracking for enterprise environments across modern and legacy data stacks.

Automates governance by propagating and ensuring data quality policies are applied across data pipelines with real-time lineage tracking.

Provides real-time monitoring of data pipelines to track quality, anomalies, and compliance posture.

Keeps data reliable and high quality with real-time anomaly detection, rules, alerts, and monitoring capabilities.

Scans and classifies sensitive data to reduce risk and ensure compliance with data protection regulations.

Developer-focused tools for integrating, configuring, and extending the AI Trust Platform.

Enterprise-grade data lineage tracking supporting broad connectivity across modern and legacy data stacks, enabling dependency-driven monitoring and impact analysis.

Native integrations with popular data platforms and tools to enable seamless AI Trust capabilities across the enterprise.

Manages metadata across data pipelines to ensure accurate, governed, and compliant AI data.

Enables monitoring configurations to be managed as code through the bigConfig framework for infrastructure-as-code approaches.

Enforces data access policies at runtime to ensure AI applications only access trustworthy and compliant data.

Security features for protecting data access, enforcing policies, and maintaining compliance across the platform.

Automated discovery and classification of PII, PHI, PCI, and other sensitive data across structured and unstructured environments.