Pluto Security vs Skyflow

About Skyflow

Skyflow sells a data privacy vault to isolate, protect, and govern sensitive data. Skyflow secures the flow of data across datastores, models, and agents. Skyflow customers span verticals like fintech, retail, travel, and healthcare. Skyflow customers use the data privacy vault architecture to comply with data residency laws, keep sensitive data out of LLMs, and govern access to PII.^[4][9]

Skyflow detects and tokenizes sensitive values at runtime in databases, documents, and analytics platforms. Skyflow replaces PII and BII across multi-modal data and keeps referential integrity. Skyflow controls the flow of PII, PHI, and PCI data at runtime and deploys AI applications in production with dynamic access controls. Skyflow governs data flowing through agents, models, and tools over MCP, A2A, or APIs.

Skyflow sits between data sources, MCP servers, agents, and models. Skyflow masks, sanitizes, and rehydrates data in real time based on policy, identity, and context. Skyflow enforces field-level privacy across MCP connections without app changes. Skyflow automatically detects, classifies, and sanitizes PII, PHI, and PCI in real time. Skyflow restores original values only where policy allows in the workflow. Skyflow ties data access decisions to agent identity and runtime context. Skyflow sanitizes sensitive data before it reaches short- or long-term memory. Skyflow works with ChatGPT, Claude, Gemini, and all major agentic frameworks. Skyflow data policies are available as a gateway proxy or embeddable SDK, and any MCP-compatible agent framework enforces them without changes to existing application code. Skyflow logs every agent data access at the field level for compliance and auditability.^[1][10][11]

Skyflow sanitizes documents at ingestion and enforces client-level controls at runtime so that AI search can be deployed on customer data. Skyflow works with Glean, Sana, Coveo, Elastic, and other AI search and knowledge platforms. Skyflow enforces data residency across 150+ countries. Skyflow detects and redacts sensitive data and intellectual property during data collection, model training, fine-tuning, RAG, and inference. Skyflow detects, isolates, and protects sensitive information flowing into and out of generative AI agents. Skyflow applies access controls around who gets access to which data and for how long.^[1][8][12]

Skyflow secures card acceptance, card issuance, customer data management, money movement, and more. Skyflow captures PII in the customer vault and passes it to any card issuance platform through a secure integration. Skyflow runs KYC/AML checks and pulls credit history by sending data directly from the vault to service providers. Fintech Data Privacy Vault includes pre-built integrations with third-party service providers such as Alloy, Experian, and Visa. Skyflow offers client-side SDKs for iOS, Android, and JavaScript that let developers collect and tokenize data.^[7][9]

Skyflow isolates, protects, and governs sensitive health data while maintaining its usability for analytics, operational workflows, and third-party data sharing. Healthcare Vault isolates, encrypts, and protects sensitive PHI and PII data, while allowing safe use and sharing. Healthcare Vault includes built-in data tokenization, masking, and redaction functions. Skyflow limits who has access to what data, and in which format. Skyflow lets teams create RBAC, ABAC, and/or PBAC policies to define how sensitive data is accessed and used. Skyflow runs analytics and ML workloads on sensitive data without decrypting it.^[13]

Skyflow is an API-first platform built by developers for developers. Skyflow allows customers to comply with data residency standards as they arise, such as GDPR, DPDP, and PIPL. Skyflow supports data residency requirements such as GDPR, the EU AI Act, and DPDP. Skyflow safeguards PII with polymorphic encryption and other built-in security features. Skyflow grants column- and row-level access in privacy-safe formats and restricts access by IP address. Skyflow lets teams train LLM models without ever decrypting sensitive data.^{[3][4][7][8][9][11][13][14]}