Vector database built for edge and on-premises
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Build locally, deploy securely, and scale with your stack
Retrieval accuracy stays above 99.4% from 1M to 10M vectors. No accuracy tradeoff as your dataset grows.
Cloud vector DBs weren’t built for edge use cases
Network latency blocks real-time applications
Cloud round-trips add 200-400ms to every query you run. You can’t build sub-100ms applications when your database contributes most of the latency.
Third-party infrastructure blocks regulated deployments
HIPAA and GDPR require your data to stay within your control. Cloud services introduce third-party processing that fails your compliance requirements.
Cloud-only architecture blocks entire deployment scenarios
Your edge devices, disconnected environments, and embedded systems can’t assume reliable internet. Cloud databases leave entire classes of your AI applications unaddressed.
Why VectorAI DB?
Built for AI that runs locally
Deploy on embedded devices, edge servers, or air-gapped facilities. Works offline and syncs when connected.
Sub-15ms local queries
Eliminate network latency. VectorAI DB search runs where your AI runs, whether on device, at the edge, or in your data center.
Build once, deploy everywhere
Use the same architecture from prototype to production, from Raspberry Pi to enterprise cloud. No environment-specific rewrites.
Your data stays yours
On-premises deployment meets GDPR, HIPAA, and data residency requirements without third-party cloud processing.
Built for developers at the edge
Build, test, and run AI where your data actually lives
Edge AI engineers
Build autonomous systems, robotics, and IoT applications that need vector search on resource-constrained devices.
Deploy to: NVIDIA Jetson, Raspberry Pi, industrial edge servers
Manufacturing teams
Run AI in disconnected factory environments for predictive maintenance, quality inspection, and production optimization.
Deploy to: Air-gapped facilities, plant floors, production lines
Build HIPAA-compliant AI that keeps patient data on-premises for clinical decision support, medical imaging, and record search.
Deploy to: Hospital data centers, clinic servers, research facilities
Manage vector search across distributed sites like retail, branch offices, and multi-region deployments.
Deploy to: Hybrid environments, edge + cloud, multi-site infrastructure
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Edge AI engineers
Build autonomous systems, robotics, and IoT applications that need vector search on resource-constrained devices.
Deploy to: NVIDIA Jetson, Raspberry Pi, industrial edge servers
-
![]()
Manufacturing teams
Run AI in disconnected factory environments for predictive maintenance, quality inspection, and production optimization.
Deploy to: Air-gapped facilities, plant floors, production lines
-
![]()
Build HIPAA-compliant AI that keeps patient data on-premises for clinical decision support, medical imaging, and record search.
Deploy to: Hospital data centers, clinic servers, research facilities
-
![]()
Manage vector search across distributed sites like retail, branch offices, and multi-region deployments.
Deploy to: Hybrid environments, edge + cloud, multi-site infrastructure
FAQ
Yes. Use the same APIs from laptop to data center. Build locally, deploy anywhere.