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Bigeye

Enterprise AI Trust and Data Observability Platform
Data & Analytics
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Bigeye

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Bigeye
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PRICING TYPE
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LANGUAGES
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AI TEHNOLOGIES
Description

Bigeye is the Enterprise AI Trust Platform built on lineage-enabled data observability technology, designed to help organizations scale their data and AI initiatives responsibly. The platform integrates data quality monitoring, end-to-end lineage, metadata management, sensitive data discovery, governance, and AI runtime enforcement into a single solution trusted by the world's largest enterprises.

The platform's data observability module delivers automated anomaly detection and data monitoring to accelerate the identification and resolution of data pipeline incidents, ensuring data reliability across complex environments. Bigeye's lineage-enabled architecture supports both modern and legacy data stacks, providing end-to-end visibility from source systems through to BI dashboards and AI applications.

Bigeye's Data Sensitivity module automatically scans and classifies PII, PHI, PCI, and other sensitive data in structured and unstructured environments, reducing regulatory risk and enabling safer AI projects. The Data Governance module streamlines data certification, stewardship, business glossary management, and semantic layer creation across teams.

AI Guardian, Bigeye's newest module, provides runtime enforcement of data access policies, ensuring AI applications only operate on trustworthy, compliant data. The platform is designed to help enterprises meet emerging AI regulatory requirements such as the EU AI Act and ISO 42001, and reduce financial, compliance, and reputational risks from compromised data. Customers report detection time reductions of 66% and significant decreases in analytics errors after deploying Bigeye.

Use cases
  • Monitor enterprise data pipelines in real time to detect anomalies before they impact business operations
  • Reduce data incident detection time from days to hours using automated observability and ML-powered alerts
  • Discover and classify PII, PHI, and PCI sensitive data automatically across structured and unstructured environments
  • Enforce runtime AI data access policies to ensure AI models operate only on trusted, compliant data
  • Manage end-to-end data lineage across modern and legacy data stacks for full pipeline visibility
  • Accelerate root cause analysis of data quality incidents using lineage-based impact tracing
  • Enable data governance teams to define quality policies, certify data assets, and maintain business glossaries
  • Help organizations meet EU AI Act and ISO 42001 compliance requirements through governed AI data workflows
  • Support data engineering teams in deploying data quality monitoring via UI or programmatic YAML configuration
  • Enable data leaders to build stakeholder trust across analytics, AI, and reporting initiatives
  • Reduce analytics errors and improve reporting accuracy for data analyst and BI teams
  • Integrate data observability with tools like dbt, Airflow, Snowflake, Databricks, BigQuery, and Tableau
Features
Anomaly detection, Data lineage, Metadata management, Data sensitivity scanning, Data governance, AI Guardian runtime, Monitoring as code, bigAI data quality, Data observability, Integrations library

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