Salt AI

dstack is an orchestration layer designed for modern ML teams, providing a unified control plane for development, training, and inference on GPUs across cloud, Kubernetes, or on-prem environments. By simplifying cluster management and workload scheduling, it eliminates the complexity of Helm charts and Kubernetes operators. The platform supports both cloud-native and on-prem clusters, with quick connections via Kubernetes or SSH fleets. Developers can spin up containerized environments that link directly to their IDEs, streamlining the machine learning workflow from prototyping to deployment. dstack also enables seamless scaling from single-node experiments to distributed training while optimizing GPU usage and costs. With secure, auto-scaling endpoints compatible with OpenAI standards, it empowers teams to deploy models quickly and reliably.

Effortlessly access powerful generative AI models with our auto-scaling APIs, zero management required. Generative AI models like stable diffusion, pix2pix and dreambooth are now an API call away. Build applications on top of such generative AI models using our scalable rest APIs which integrate seamlessly and come at a fraction of the cost of other alternatives. Seamless integrations with your existing systems, without the need for extensive development. Easily integrate our APIs into your workflow with support for stacks like CURL, Python, Node.js and PHP. We access the unused computing power of millions of decentralised crypto mining rigs worldwide and optimize them for machine learning and package them with popular generative AI models like Stable Diffusion. By harnessing these decentralized resources, we can provide you with a scalable, globally accessible, and, most importantly, affordable platform for Generative AI delivered through seamlessly integrable APIs.