The Technology
SwarmOne.ai is the first-ever Autonomous AI Infra Platform—covering AI model training (including nocode training), model evaluation, and model deployment. The platform provides enterprises with the fastest way to train, evaluate, and deploy AI models, integrating seamlessly into existing workflows while giving them full control over their compute resources.
By leveraging breakthrough technologies, SwarmOne significantly simplifies and speeds up the entire AI lifecycle. Whether instant model fine-tuning is required, batch inference for large-scale evaluation, or optimized model deployment, SwarmOne streamlines all these tasks by orders of magnitude.
This is all achieved with just two lines of code on the user side and one-click installation on the hardware side.
evaluation & deployment
Hugging Face
How does it work
SwarmOne is an Autonomous AI Infra Platform built to abstract away the heavy lifting of DevOps, MLOps, and SecOps. It enables AI developers and data scientists to focus exclusively on training, evaluation, and inference, rather than infrastructure. At the heart of the platform is a lightweight client that performs a real-time “workload X-ray” on your models, datasets, parameters, and environment.
This analysis feeds into SwarmOne’s autonomous scheduling engine that makes intelligent decisions on where and how to run the workload.
The platform’s most distinctive feature is that it disaggregates the hardware from the user experience, beginning with a one-click install on GPU nodes. Whether you’re training on local infrastructure, major cloud GPUs, or leveraging SwarmOne’s own compute burst mode, the developer experience remains consistent.
SwarmOne Studio – a no-code solution running on your own compute – lets enterprise teams build and deploy models using a seamless interface, eliminating the need for ML framework expertise. The stack is model-agnostic, allowing you to support proprietary architectures without any manual optimization.
Technically, SwarmOne deploys a new, futuristic stack that starts above CUDA, all the way to the user interface – which just works. It applies cutting-edge optimization techniques (like DeepSpeed, Axolotl, and gradient checkpointing) tailored dynamically per workload, based on model type, data dimensions, precision settings, and available infrastructure.
The result is high throughput, reduced runtime, and lower operational overhead – all achieved without modifying the user’s code. Monitoring and observability are built-in via native integrations with popular experiment tracking tools.
Added Value for the Data Center / Neo-Cloud
Data centers and neo-clouds often face intense competition when offering AI-oriented services. Because GPU performance and operational costs are often similar among providers, they may rely on price alone to compete, lacking a true software differentiator.
Adding insult to injury, while incumbent clouds maintain sky-high hourly prices for an 8-GPU H100 node, neo-clouds have no competitive tool beyond undercutting on price.
By adding SwarmOne to their offerings, data centers/neo-clouds gain a significantly more valuable and differentiated solution. SwarmOne delivers a far superior model training, evaluation, no-code, and inference experience in terms of simplicity, efficiency, and cost savings—unmatched by any commodity “instance-based” offering. Additionally, it helps customers reduce costs and accelerate research and production to a level unattainable with conventional methods.
No Docker. No MLOps nor DevOps
Data scientists’ time spent exclusively on science
Autonomous GPU & workload utilization
Maximize return on your AI investment
