Multi-cloud AI integration

Multi-cloud AI integration involves running AI/ML workloads across multiple cloud providers, leveraging unique strengths from each platform. Xebia helps organisations design portable and cloud-agnostic AI architectures.

What Are the Key Benefits of Multi-cloud AI integration?

Enables access to diverse AI/ML tools across clouds.
Reduces dependency on a single provider.
Improves resilience with distributed workloads.
Optimizes cost by selecting the most efficient platform per task.
Requires mature pipelines and governance—areas where Xebia provides expertise.

What Are Some Multi-cloud AI integration Use Cases at Xebia?

Training ML models on one cloud for performance and running inference on another for latency benefits.
Creating data pipelines using storage and processing resources from multiple clouds.
Deploying portable ML models using Kubernetes and model registries.
Using multi-cloud MLOps platforms for consistent experimentation and monitoring.
Integrating specialised AI services from different clouds into a single application workflow.

Related Content on Multi-cloud AI integration

‌