Add Multimodal Search to Your Apps with Cloud‑Hosted GPUs.
Generate embeddings for images and text, build a vector index, and serve blazing‑fast search without maintaining on‑prem hardware.
Why Use CloudRift for
Multimodal Search?
Embedding and reranking workloads need low-latency, GPU-accelerated infrastructure. CloudRift lets you choose: run your own stack on rented GPUs, or deploy via managed inference endpoints. Scale workers as traffic grows — your stack, your pace.
- ✓ Image + text embeddings
- ✓ VM or container flexibility
- ✓ No local installs
- ✓ Scale to multi‑GPU
How It Works
Run on Rented GPUs
Spin up your own stack using RTX 4090, 5090, or 6000 Pro. Full control over models, containers, and workflows.
Use Managed Endpoints
Skip infra setup with OpenAI-compatible endpoints for embeddings and reranking. Fast to launch, easy to scale.
Mix and Match
Start with inference, switch to self-hosted when needed—or run both in parallel. CloudRift gives you options.
What our Partners say
From customers scaling embeddings on CloudRift.
Aamir Shakir
Co-founder @ Mixedbread
We're using CloudRift at Mixedbread to run the inference for our state-of-the art embedding & machine learning models. The service is amazing, it is extremely stable, the GPUs are affordable & provision fast. Also the specs around the GPUs such as CPU, Memory and Network are the best. We really enjoy the personal & fast support.
