Firecracker microVM

QEMU microVM launcher for low-latency RVF cognitive containers in RuVector stack, enabling secure on-device vector processing for edge AI environments.

Perpetual sandbox platform for AI agents that achieves sub-25ms resume times from standby mode with infinite state persistence and zero compute charges during idle periods.

Open-source cloud infrastructure providing secure sandboxes for AI agents to run code in isolated environments. Sandboxes start in 80ms and support Python, JavaScript, Ruby, and C++ on Linux.

Architectural patterns for isolating and managing data for multiple customers (tenants) in shared vector database infrastructure. Multi-tenancy strategies include namespace isolation, metadata filtering, and separate collections, each offering different trade-offs between performance, cost, and data isolation.

Architectural patterns for isolating data between different tenants (customers/organizations) in vector databases. Includes collection-per-tenant, partition-per-tenant, and filter-based approaches with different trade-offs.

Privacera AI Governance (PAIG) is a solution designed to secure and govern AI data, including safeguarding vector databases and embeddings, ensuring data privacy and compliance for AI applications.