Actian VectorAI DB

Actian VectorAI DB is a portable vector database designed for edge and on‑premises deployments, enabling retrieval‑augmented generation and semantic search without relying on cloud services. It stores embedded vectors locally, allowing AI agents to query data with sub‑15 ms latency and high throughput—reported at 1.9 k queries per second for ten million vectors—while maintaining 99 % recall at scale. The system operates offline, synchronizing only when a network connection is available, which makes it suitable for embedded devices, factory floors, and air‑gapped environments.

The database targets developers who need real‑time AI applications that cannot tolerate the 200‑400 ms round‑trip delays typical of cloud‑based vector stores. By keeping data and infrastructure under the user’s control, it addresses regulatory constraints such as HIPAA and GDPR, and it avoids third‑party processing that could expose sensitive information. Its architecture supports multi‑modal embeddings and integrates with common development languages, allowing a single codebase to be deployed across devices, edge servers, or data centers.

Actian VectorAI DB positions itself as a local‑first alternative to cloud‑only vector databases, promising consistent performance from prototype to production and rapid installation—claiming a transition from install to production in minutes. It is marketed toward enterprises requiring secure, low‑latency AI retrieval in regulated or disconnected settings.