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Ensure your AI data is accurate, governed, and compliant — so you can scale your AI responsibly.

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Bigeye is the Enterprise AI Trust platform that improves data and AI visibility, accelerates AI deployments, and promotes stakeholder trust.

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Adrianna Vidal

Adrianna Vidal is a writer and content strategist at Bigeye, where she explores how organizations navigate the practical challenges of scaling AI responsibly. With over 10 years of experience in communications, she focuses on translating complex AI governance and data infrastructure challenges into actionable insights for data and AI leaders.

At Bigeye, her work centers on AI trust: examining how organizations build the governance frameworks, data quality foundations, and oversight mechanisms that enable reliable AI at enterprise scale.

Her interest in data privacy and digital rights informs her perspective on building AI systems that organizations, and the people they serve, can actually trust.

recent Posts from this author

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AI is Reshaping CDO Leadership: What You Need to Know

This recap breaks down what CDOs need to know to stay ahead.

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Our 2025 Data Observability Trends and Predictions

Based on industry movements and customer conversations, here’s what we expect in the year ahead.

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Data Leaders’ 2025 Toolkit: Must-Have Observability Resources

With the complexity of enterprise data pipelines, ensuring trust in data is crucial. But where do you start?

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Achieving Data Transparency at Scale: Freedom Mortgage’s Success with Bigeye

We spoke with Eric Chesebro, executive vice president of data governance at Freedom Mortgage, to discuss how they’ve transformed their data governance strategy using Bigeye.

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Data Observability vs. Data Quality: Key Differences

Discover the critical roles of and key differences between data observability and data quality.

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What is Data Quality Testing?

Discover what data quality testing is, why it matters, and techniques to ensure your data is accurate, consistent, and reliable.

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