Parasail Launches First AI Deployment Network to Deliver On-Demand Compute Power for AI Companies
Parasail has launched the world's first AI Deployment Network, with a vision to transform the way AI firms acquire and scale compute power. Focusing on performance, flexibility, and affordability, the platform gives immediate access to high-performance GPUs like H100s, H200s, A100s, and 4090s, enabling teams to quickly develop, test, and deploy AI models at scale without conventional limitations.
In contrast to traditional cloud vendors that bind clients into long-term contracts, Parasail provides an on-demand, contract-free solution. Its intelligent orchestration engine dynamically routes workloads across its global network to deliver the best possible performance and cost optimization. The system ensures compute is used only when needed, eliminating unnecessary idle resource expenses.
Challenging the Cloud Status Quo
Mike Henry, Parasail’s co-founder and CEO, said, “Most cloud providers make the false promises of on-demand compute, and they fail to deliver on that promise.”
He added, “In reality, legacy cloud providers use small amounts of compute capacity to lure customers into long-term contracts. At Parasail we are providing the first real-time, true on-demand access to massive compute without the hidden constraints.”
The company has raised $10 million in seed funding from Basis Set Ventures, Threshold Ventures, Buckley Ventures, and Black Opal Ventures.
Plug-and-Play AI Deployment at Scale
Parasail’s platform allows companies to launch production-ready endpoints using dozens of GPUs in a matter of hours, streamlining inference workflows and enabling faster deployment of large language models (LLMs). Companies switching from providers like OpenAI or Anthropic can reportedly cut inference costs by 15–30x, and gain a further 2–5x cost advantage compared to other open-source alternatives.
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Several AI-first companies have benefited from deploying with Parasail. Elicit accelerated its research by screening 100,000 papers daily, while Rasa launched real-time models in Europe, enabling free public access. Everpilot reduced inference costs by 10x, and Weights & Biases scaled DeepSeek’s capacity. Oumi streamlined batch data generation, reducing effort in managing large datasets.
