Skyflow has announced the launch of its Runtime AI Data Security platform for AWS AgentCore. This integration aims to enable agentic AI workflows to transition from prototypes to production environments, addressing security, privacy, and global regulatory compliance challenges.
While advancements in AI models and significant industry investments are ongoing, many organizations encounter difficulties in deploying agentic applications beyond demos and prototypes. Enterprises, along with the startups and Independent Software Vendors (ISVs) serving them, require robust methods to protect sensitive customer data as they implement agentic applications in production. Key requirements for these real-world agentic workflows include preventing data leakage, meeting global compliance standards, and enforcing contextual data usage by agents. Traditional data security and newer AI security posture management tools often block or redact sensitive data, which can impede the very automation agents are designed to perform.
Skyflow’s platform seeks to overcome these obstacles by protecting data in use through fine-grained controls. This approach allows sensitive customer data to remain protected, governed, and auditable even when actively processed by AI agents and models, moving beyond simple redaction and blocking mechanisms.
AWS has recently introduced new offerings for agentic AI, including Amazon Quick Suite and Amazon Bedrock AgentCore. Amazon Quick Suite is an agentic AI application designed to assist employees with insights, research, task automation, data visualization, and cross-application actions. Amazon Bedrock AgentCore serves as a platform for securely building, deploying, and operating scalable agentic systems. Skyflow’s Runtime AI Data Security solution is integrated with these AWS offerings to establish a secure-by-design foundation for agentic AI.
This integration provides runtime, field-level, contextual, and identity-aware protections for sensitive data such as Personally Identifiable Information (PII), Protected Health Information (PHI), and Payment Card Industry (PCI) data. For instance, with Amazon Quick Suite, Skyflow enforces runtime sensitive data protection by inspecting and de-identifying PII/PHI before it reaches any agent or model, thereby ensuring compliance with regulations like GDPR and HIPAA as data traverses systems. With Amazon AgentCore, Skyflow integrates with agent identity binding and enforces policy-based data access at runtime, ensuring agents only access the “minimum necessary” data and providing field-level logging for comprehensive auditability.
Andy Perkins, General Manager, US ISV sales – Data, Analytics, GenAI at AWS, commented, “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.”
As AI transitions from simple Large Language Model (LLM) calls to fully autonomous, multi-step agents, enterprises face a challenge: agents require access to sensitive data to complete workflows, but traditional blocking, redacting, or monitoring tools can prevent agents from performing their functions, leading to stalled pilots. Skyflow’s Runtime AI Data Security provides a data-first, privacy-trust layer within the AI data flow path. Leveraging Skyflow’s patented polymorphic engine, the solution keeps sensitive data protected while enabling AI systems to use it productively and compliantly. Its capabilities include real-time discovery, classification, and de-identification of sensitive data (PII, PHI, PCI) with entity preservation, allowing models and agents to reason, match, and act meaningfully. It also offers rehydration, which is the fine-grained, governed restoration of original values only at the exact point in a workflow where it is permitted and required. Additionally, the platform provides Global Data Residency and Sovereignty Controls, context-aware governance and policy enforcement binding identity to each agent, entity-preserving transformations for secure embeddings and governed vectorization, and comprehensive, field-level auditability.
Anshu Sharma, CEO of Skyflow, stated, “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.”
Skyflow’s Runtime AI Data Security solution aims to ensure sensitive data moves securely at the speed of AI. By combining Amazon Quick Suite and AgentCore with Skyflow’s foundational data security and governance, enterprises can advance responsible innovation. Skyflow operates as a security and privacy platform for the modern AI data stack, designed to simplify how companies isolate, protect, and govern customer sensitive data through its Data Privacy Vault. The company is backed by investors and works with Fortune 500 and growth companies across various sectors, including financial services, healthcare, travel and hospitality, and retail.
