Govern & Secure the Data Fueling Your GenAI & LLM Initiatives

Ensuring the integrity of GenAI input data is vital, as model output verification is often unfeasible.

With Bedrock’s Metadata Lake at the core, you gain deep insight into the origin, sensitivity, and movement of data feeding your AI models. This rich, contextual metadata enables dynamic tagging, policy implementation, and auditability, ensuring your AI systems are built on trusted, compliant data.

<49%

Of organizations are highly confident in their ability to control sensitive data used for AI/ML training.

>60%

Of organizations identify classifying sensitive AI data, AI entitlement control, and tracking AI data as their top 3 AI security hurdles.

<48%

Of organizations express high confidence in their ability to control sensitive data used for AI/ML training.

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One Platform to Govern & Secure the Data Behind Your GenAI & LLM Initiatives

Know What Data Is Used In AI training & Inference

Bedrock Security aggregates metadata across cloud, SaaS, and on-prem environments, creating a single source of truth for data classification, residency, and access control.

Data Provenance Tracking

Understand where training data comes from and how it’s transformed.

Sensitive Data Discovery

Identify and tag PII, PHI, and proprietary content before it’s used in AI.

Minimize GenAI Risks With Strong Data Controls

Prevent unintended data leakage, model bias, or compliance violations by enforcing security policies directly on your GenAI workflows.

AI Dataset Governance

Ensure that only approved data is used for training and inference.

Bias and Drift Monitoring

Track data quality and changes over time to maintain model reliability.

Streamline Policy Enforcement & Maintain Compliance

AI innovation doesn’t have to mean compliance gaps. Bedrock Security automates tagging, governance, and reporting for all GenAI-related data activities.