Sold by: Skyflow
Deployed on AWS
Skyflow secures the flow of data across data stores, models, and agents. Enterprises turn to Skyflow as their runtime AI data control layer to protect sensitive data, enable safe AI deployment, and unlock full value from their applications, data platforms, and AI systems.
Overview
AI security needs data security. Skyflow is the runtime AI data control layer that secures the flow of sensitive data,PCI, PHI, PII, and unstructured files, across datastores, models, apps, and agents. As enterprises deploy LLMs and agentic AI into production, Skyflow protects sensitive data at every stage: ingestion, training, and inference.
Enterprises deploy AI safely with Skyflow. Agents, models, and MCP servers access real customer data while PII remains protected. Skyflow enforces access at runtime with dynamic, context-aware controls and field-level governance, so the same workflow can return full values to an authorized user and de-identified values to the right user at the right time. AI projects move from pilot to production without waiting on a security exception. Skyflow combines:
- PII Detection & Discoverability. Automatically find and classify sensitive data across structured and unstructured sources, so nothing slips into a model, prompt, or agent workflow unseen.
- AI Data Sanitization. De-identify, tokenize, and mask sensitive data before it reaches a model or agent, protecting it at rest, in transit, and in use.
- Contextual Accuracy & Usability. Preserve data utility through polymorphic tokens that reveal only the minimum viable information required for each specific context. Same data takes different forms based on who's accessing it and why
- Runtime Protection. Enforce policy based, zero trust access control across every data flow between datastores, models, and agents, dynamically, at the point of use.
Fortune 500 companies including ServiceNow, Kearney, GoodRx and Visa trust Skyflow to protect sensitive data at scale while preserving data utility through polymorphic encryption. The platform delivers built-in compliance support for HIPAA, GDPR, PCI DSS, and emerging AI regulations, so teams can move from data risk to safe AI deployment in days, not months.
Secure data. Unblock AI.
Learn more at <www.skyflow.com >. For custom pricing and annual commitments, contact aws@skyflow.com .
Highlights
- Ship AI without shipping your PII. Skyflow is the runtime data control layer that detects, de-identifies, and tokenizes PCI, PHI, PII, and unstructured files before they ever reach a model, prompt, or agent.
- Zero-trust access enforced at the point of use. Policy-based, role-aware controls with field-level governance return full values to authorized users and de-identified values to everyone and everything else, across every flow between datastores, models, apps, and agents.
- Compliance without sacrificing data utility. Polymorphic encryption preserves the format and referential integrity AI systems need to stay accurate, with built-in support for HIPAA, GDPR, PCI DSS, and emerging AI regulations, so teams go from data risk to safe deployment in days.
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Email support at support@skyflow.com .
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Encryption and Tokenization
Polymorphic encryption and tokenization engine that encrypts, tokenizes, and masks sensitive data at rest, in transit, and in use.
Data Isolation
Segregated, privileged-access environment that isolates sensitive data and eliminates sensitive data replication across infrastructure.
Access Control and Governance
Policy-based, role-based, and attribute-based access control to manage data visibility, control who sees what data, when, and where, with centralized management from one location.
Compliance Framework Support
Built-in support for GDPR, Schrems II, BDSG, PCI, HIPAA, and data residency requirements.
Data Residency and Deployment Flexibility
Ability to deploy the vault in specific geographic locations to satisfy data residency requirements without replicating entire infrastructure across regions.
Fine-Grained Data Access Control
Dynamic, fine-grained access control on AWS services including Amazon Redshift, Amazon S3, Amazon SageMaker, and Amazon EMR using de-identification, hashing, masking, and privacy enhancing technologies (PETs).
Sensitive Data Discovery and Classification
Automated sensitive data discovery capabilities to tag and classify sensitive data in AWS with highly accurate metadata generation for data security purposes.
Policy Management and Enforcement
Write data security policies once in plain language or as-code and enforce them consistently across multiple AWS data sources without copying or moving data.
Attribute-Based Access Control
Attribute-based access control (ABAC) implementation to simplify and streamline data security policy management across connected data sources.
Data Activity Monitoring
Real-time continuous monitoring of data and user query behavior to track activity, identify risky patterns, and enable proactive policy updates.
Sensitive Data Discovery
Automated and centralized sensitive data discovery across entire data and analytics estate with universal coverage
Fine-Grained Access Control
Fine-grained access controls enforced across all cloud services with distributed policy enforcement points
Data Masking and Encryption
Data masking, encryption, and decryption capabilities for protecting sensitive information
Centralized Audit and Compliance
Comprehensive audit logging and centralized audit service with out-of-box customizable reports and dashboards for compliance purposes
Fully-Managed Infrastructure
Fully-managed SaaS infrastructure with automatic maintenance, upgrades, and software installations without manual user processes
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