Skyflow Launches AI Runtime Data Security for AgentCore and Quick Suite

While AI models are improving every few months and the industry is investing hundreds of billions of dollars on AI infrastructure, most organizations still struggle to move from demos and prototypes to production-grade agentic applications.

As enterprises and the startups and ISVs that serve them begin deploying agentic applications in production, they need a reliable way to protect sensitive customer data. Preventing data leakage, meeting global compliance requirements, and enforcing which data an agent can use in which context are now foundational requirements for any real-world agentic workflow.

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Traditional data security and newer AI security posture management tools can only block or redact sensitive data – stopping agents from completing the very workflows they’re meant to automate.

Skyflow removes these roadblocks by protecting data in use with fine-grained controls that go far beyond simple redaction and blocking. Sensitive customer data remains protected, governed, and auditable even when actively processed by agents and models.

AWS and Skyflow: Better together

AWS recently released new offerings for agentic AI—Amazon Quick Suite and Amazon Bedrock AgentCore.

Amazon Quick Suite is AWS’s agentic AI application that helps employees transform how they find insights, conduct deep research, automate tasks, visualize data, and take action across applications. Amazon Bedrock AgentCore is an agentic platform to build, deploy, and operate highly capable agents securely at scale.

Skyflow is launching its Runtime AI Data Security solution integrated with these AWS offerings to provide a secure-by-design foundation for agentic AI.

This integration delivers runtime, field-level, contextual and identity-aware protections for sensitive data (PII, PHI, PCI). For example:

• With Amazon Quick Suite, Skyflow enforces runtime sensitive data protection, inspecting and de-identifying PII/PHI before it reaches any agent or model, while ensuring compliance with regulations like GDPR and HIPAA as data flows across systems.
• With Amazon AgentCore, Skyflow integrates with agent identity binding and enforces policy-based data access at runtime. This ensures agents only access the “minimum necessary” data and provides field-level logging for complete auditability.

“Agentic AI is rewriting how enterprises use data, but it demands a new level of protection when autonomous agents interact with sensitive information. At AWS, security has always been our top priority—it’s the foundation of everything we build. AWS Quick Suite and AgentCore enable organizations to operationalize AI at scale, and integrating Skyflow adds the fine-grained data protections and agent-level governance required in regulated industries. This combination helps customers move from pilots to production with confidence, knowing their most sensitive data remains protected at every step.”

— Andy Perkins, General Manager, US ISV sales – Data, Analytics, GenAI

Unblocking Agentic Workflows with Skyflow’s Runtime AI Data Security

As AI shifts from simple LLM calls to fully autonomous, multi-step agents, enterprises face a core challenge: agents need access to sensitive data to complete workflows — but traditional tools that only block, redact, or monitor prevent the agent from doing its job. The result is stalled pilots and brittle demos that can’t make it to production.

Skyflow’s Runtime AI Data Security provides a data-first, privacy-trust layer inside the AI data flow path. Powered by Skyflow’s patented polymorphic engine, it keeps sensitive data protected while still allowing AI systems to use it productively and compliantly.

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Key capabilities include:

• Real-time discovery, classification, and de-identification of sensitive data (PII, PHI, PCI) with entity preservation so models and agents can still reason, match, and take meaningful action.
• Rehydration: Fine-grained, governed restoration of original values only at the exact point for a specific task in a workflow where it is permitted and required, allowing agents to finish end-to-end tasks without overexposing sensitive data.
• Global Data Residency and Sovereignty Controls, ensuring sensitive data never leaves its jurisdiction. Even when agents, MCP servers, or models run globally, Skyflow enforces in-region processing and cross-border restrictions automatically.
• Context-aware governance and policy enforcement, binding identity to each agent and enforcing “minimum necessary” access based on user, agent, purpose, data type, and regulatory rules.
• Entity-preserving transformations, including secure embeddings and governed vectorization, enabling safe retrieval, RAG, orchestration, and agentic workflows without exposing raw data.
• Comprehensive, field-level auditability, recording every access, transformation, residency decision, and rehydration event for internal governance, verifiability and regulatory compliance.

With Skyflow, agentic AI workflows can finally move from prototypes to production — delivering automation without compromising security, privacy, or global regulatory requirements.

“The success of agentic AI depends on absolute trust and data security when agents handle sensitive enterprise data. Skyflow’s Runtime AI Data Security provides the essential guardrails—protecting data exactly at the moment of use. This enables enterprises to safely scale from cautious AI pilots to full production, supporting the AWS agentic AI mission.”

Anshu Sharma, CEO, Skyflow Skyflow’s Runtime AI Data Security solution ensures sensitive data moves safely at the speed of AI. By combining Quick Suite and AgentCore with Skyflow for fundamental data security and governance, enterprises unlock responsible innovation.

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