GPU Infrastructure for Multimodal Search
Generate embeddings for images and text, build vector indices, and serve low-latency search pipelines on GPU-accelerated infrastructure.
Request DemoWhy CloudRift
Purpose-Built for Embedding Workloads
Embedding and reranking workloads require low-latency, GPU-accelerated infrastructure. CloudRift lets you deploy your own stack on dedicated GPUs or use managed inference endpoints — and scale workers as traffic grows.
- Image + text embeddings
- VM or container flexibility
- Persistent storage
- Scale to multi-GPU
Workflow
How It Works
Generate Embeddings
Deploy open embedding models to encode images and text into vector representations on GPU-accelerated infrastructure.
Build Your Index
Store embeddings in a vector database and configure reranking for high-precision multimodal search results.
Serve and Scale
Deploy your search pipeline on managed inference endpoints or dedicated instances. Scale workers as query volume grows.
Partner Spotlight
What Our Partners Say
“We're using CloudRift at Mixedbread to run the inference for our state-of-the-art embedding and machine learning models. The service is amazing — extremely stable, the GPUs are affordable and provision fast. The specs around CPU, memory, and network are the best. We really enjoy the personal and fast support.”
Aamir Shakir
Co-founder @ Mixedbread
FAQ
Frequently Asked Questions
Ready to get started?
Get in touch with our team to discuss your requirements and find the right solution for your infrastructure.