VM-X is a routing and management layer for AI.
Common questions our users face are:
- How do I reduce my inference cost and increase model performance?
- Which models are best for my use case, and what providers should I run them on?
- How can I manage AI resource use across my different applications, teams, processes so that high priority tasks always get executed?
- How does model performance vary across providers? Is this provider/model robust and reliable enough to build my application on?
- What security measures can I deploy across my model infrastructure?
This is where VM-X comes in. It simplifies the management of AI models, enabling you to manage allocation, routing, fallback, and security of AI workloads.