Nscale provides a GPU cloud platform optimized for AI workloads, featuring on-demand compute and inference services, dedicated training clusters, and scalable GPU nodes. The platform addresses the high costs and inefficiencies associated with AI model training and deployment by offering a fully integrated infrastructure powered by renewable energy in Europe.
Funding
$3.3B raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
SCFounders
Product
Problem
Training and deploying AI models can be computationally expensive and inefficient, requiring specialized infrastructure and expertise. Many organizations struggle to access the necessary resources and manage the complexities of AI workloads, leading to increased costs and slower development cycles.
Solution
Nscale provides a full-stack AI cloud platform designed to optimize AI workloads, offering on-demand compute, inference services, and dedicated training clusters. The platform features a fully integrated suite of AI services and compute resources, including a marketplace for AI/ML tools, serverless model endpoints for inference, and optimized GPU clusters for training. Nscale's infrastructure is built for AI, featuring high-performance GPU nodes, low-latency networking, and fast storage, all powered by renewable energy. By managing every aspect of the AI infrastructure stack, Nscale enables organizations to reduce costs, accelerate development, and efficiently scale their AI initiatives.
Target Audience
Nscale targets organizations across various industries, including software and technology, finance, manufacturing, and research, that require high-performance computing resources for AI model training, inference, and development.
Features
- On-demand GPU compute and inference services for flexible resource allocation
- Serverless API endpoints for instant and scalable Generative AI inference
- Dedicated training clusters with Slurm and Kubernetes support for containerized workloads
- High-performance GPU nodes with AMD and NVIDIA options, optimized for AI and HPC tasks
- Low-latency networking with RoCE and non-blocking design for efficient collective operations
- Fast storage with RDMA enabled parallel filesystems for rapid data loading and checkpointing
- AI Marketplace offering access to various AI/ML tools and resources
- Datacenters powered by 100% renewable energy