Data Security · Founded by Aaron Fulkerson & Prof. Raluca Ada Popa in 2021

Opaque Systems

A confidential AI platform that lets enterprises run AI and analytics on sensitive data securely—using hardware-backed privacy, policy enforcement, and auditability.

Cost

Demo, Paid

Rating

★ People love it

Time to value

Moderate Setup (1-3 days/weeks, depending on data sources & compliance needs)

You can use OPAQUE when you need to use proprietary, regulated, or sensitive data for AI/ML (like RAG, analytics, or multi-agent systems) without leaking anything. It supports workflows in Python, Spark, REST APIs, and no-code interfaces; enforcement of governance policies; and logs/audit trails that are cryptographically verifiable. Strong use cases include fraud detection, private LLMs, secure analytics across data silos, or bringing AI into environments where compliance is critical.

What Opaque Systems does

Run ML/AI workloads on encrypted data using trusted execution environments (TEEs)Enforce policies (role-based, region-based, governance) throughout AI pipelinesCreate confidential agents for RAG (Retrieval-Augmented Generation)Generate cryptographically signed audit logs and proofs of complianceIntegrate seamlessly via REST APIs, notebooks, Spark, PythonDeploy in Azure/GCP/cloud or private cloud with privacy guaranteesHardware-backed attestation: ensures code and runtime are trusted before data is processed inside enclavesEncrypted data in use (not just at rest or transit) during AI/ML modelling & analyticsPolicy enforcement built-in: redaction, role/region-based access, prompt sanitization, etc.Verifiable audit trails & cryptographic logs for compliance and governanceSeamless integration with existing AI/analytics stack (Python, Spark, REST), plus support for deploying on Azure/GCP or private cloudConfidential Agents for RAG workflows with built-in privacy protections