Scaling agentic AI: How UiPath built its high-performance GPU platform on AI Hypercomputer

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As a market leader in enterprise agentic automation and business orchestration, UiPath is helping to pioneer an industry shift toward agentic AI. With it, the company is deploying autonomous agents to actively reason, make decisions, and execute complex business processes across its disparate systems.  This transition from simple task automation to cognitive decision-making agents requires a massive surge in computational power and powerful infrastructure that’s reliable enough for the needs of the world's largest enterprises. Being able to orchestrate hundreds of GPUs in perfect harmony can be what makes the difference between just running a research experiment and building a global AI platform. Such orchestration requires balancing massive training jobs with real-time inference, all without letting costs spiral or latency spike.

To do so, UiPath re-architected its infrastructure to support high-scale intelligent document processing (IDP) using UiPath IXP and moved from isolated clusters to a shared Google Cloud GPU fleet, balancing A3 VM instances (NVIDIA H100 GPUs) for training with G4 VM instances (NVIDIA RTX Pro 6000) for inference. This architecture lets UiPath solve its “spiky workload” problem and count on predictable costs and open-source patterns that the company’s engineering teams can use to replicate this architecture themselves. "Realizing the full potential of enterprise agentic AI requires an infrastructure that matches our ambition. Google Cloud provides the scale and flexibility we need to train specialized models …

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