DigitalOcean Powers Workato's Agentic Enterprise with Production-scale AI
MWN-AI** Summary
DigitalOcean has unveiled a significant optimization for Workato’s AI Research Lab through its Agentic Inference Cloud, which is powered by NVIDIA GPUs. This vertically integrated, inference-optimized platform is designed specifically for production-scale AI workloads. Workato's research efforts have reported impressive performance enhancements after migrating their AI workloads to DigitalOcean, including a 67% reduction in inference costs, a 77% faster time-to-first-token, and a 67% increase in throughput.
The collaboration has been particularly successful in advancing Workato's frontier models, notably Llama-3.3-70B, which saw its inference cost drop to $0.77 per million tokens. With DigitalOcean, Workato has managed to accelerate their time-to-value from weeks to mere days, effectively doubling their operational efficiency. This transformation equips thousands of global customers—who rely on Workato’s ONE platform for enterprise AI deployment—with the capability to build and govern AI agents effectively across their organizations.
DigitalOcean's Agentic Inference Cloud offers superior compute resources while abstracting complexities associated with infrastructure management. The use of NVIDIA Dynamo for load balancing further enhances efficiency by directing workloads to optimal compute resources in real-time. This improved orchestration has significantly contributed to higher throughput and lower operational costs, vital for companies navigating the challenges of scaling AI inference.
In summary, the joint initiative between DigitalOcean and Workato exemplifies how optimized cloud infrastructure can enable rapid advancements in AI technologies, establishing a framework for companies looking to leverage AI at scale. DigitalOcean's focus on providing predictable economics and streamlined operations enhances Workato's ability to innovate continuously in the evolving landscape of enterprise AI.
MWN-AI** Analysis
In a rapidly evolving landscape driven by artificial intelligence, DigitalOcean's (NYSE: DOCN) recent partnership with Workato is a notable development, particularly its innovative Agentic Inference Cloud, which is tailored for production-scale AI. This collaboration demonstrates significant performance enhancements and operational cost reductions, positioning DigitalOcean as a key player in the enterprise AI arena.
Workato's impressive metrics—67% higher throughput and 67% lower inference costs after migrating to DigitalOcean—suggest a strategic advantage for organizations considering a switch to this platform. The use of NVIDIA Hopper GPUs within DigitalOcean’s infrastructure has not only accelerated task performances but also dramatically reduced operational complexities, enabling teams to focus on research and development rather than infrastructure management.
As demand for AI solutions heightens, particularly for those that require intense computational resources, companies leveraging DigitalOcean’s optimized platform may witness enhanced scalability and cost efficiency. In particular, the reduction of inference costs to $0.77 per million tokens allows for improved margins—an essential factor as more enterprises scale their AI deployments.
Investors should remain vigilant as AI adoption accelerates globally. DigitalOcean’s strategy of enabling seamless integration of inference capabilities with fundamental cloud services could drive sustained operational efficiencies, appealing to a broad spectrum of digital-native businesses.
From a market standpoint, those considering investments in digital infrastructure or AI as a service should closely monitor DigitalOcean’s trajectory and its partnerships. The potential for recurring revenue streams from AI enterprises, alongside DigitalOcean’s focus on abstraction of complexity and superb performance, positions the company for a favorable outlook. Thus, DigitalOcean presents a compelling investment opportunity amid the AI boom, as it empowers enterprises to innovate and scale effectively.
**MWN-AI Summary and Analysis is based on asking OpenAI to summarize and analyze this news release.
Workato’s AI Research Lab achieves 67% higher throughput, 77% faster time-to-first-token, and 67% lower inference costs on DigitalOcean’s Agentic Inference Cloud, powered by NVIDIA
DigitalOcean (NYSE: DOCN), the Agentic Inference Cloud built for production AI, today announced that Workato ’s AI Research Lab is using its vertically integrated, inference-optimized platform, accelerated by NVIDIA Hopper GPUs, to advance the development of its next-generation enterprise AI agents while materially improving performance, cost efficiency, and deployment speed.
After moving its AI Labs workloads to DigitalOcean, Workato achieved immediate gains for frontier models, including Llama-3.3-70B:
- Inference cost: $0.77 power 1M tokens – 67% lower
- Throughput: 13,561 tokens per second per GPU – 67% higher
- Time-to-First-Token (TTFT): 1,455 ms at high load – 77% faster
- Time-to-Value: Reduced from weeks to days – 2X+ acceleration
With thousands of customers globally deploying over 1 trillion tasks since 2013, the Workato ONE platform enables customers to build, deploy, and govern AI agents at an enterprise scale. Built on a decade of integration expertise spanning 14,000+ applications, Workato's platform enables organizations to move from simple automation to agentic AI that can reason, act, and orchestrate work across the entire business.
To support that vision, Workato AI Research Lab required infrastructure capable of handling distributed training and sustained, reasoning-heavy inference under real production load. Not only was DigitalOcean able to provide high-performance NVIDIA Hopper GPUs faster than any other provider for the team to begin their work, but the Workato AI Research Lab team quickly discovered the significant performance boost and TCO improvement as a result of DigitalOcean’s inference-optimized architecture and simplified experience.
“Before DigitalOcean, we didn’t have a dedicated solution for in-house training and multi-node serving, and that was a major blocker for AI research,” said Oscar Wu, AI Research Scientist at Workato. “DigitalOcean was the fastest provider to get us up and running, enabling us to advance our AI programs. The collaboration on performance optimization coupled with the support from the DigitalOcean team of solutions architects, accelerated our progress by roughly two to three times.”
Working closely with Workato, DigitalOcean helped design and tune a distributed inference architecture on DigitalOcean Kubernetes (DOKS) . As part of this collaboration, DigitalOcean configured NVIDIA Dynamo to intelligently coordinate workloads across interconnected GPU clusters. This ensured requests were routed to the most efficient compute resources in real time, reducing redundant processing, lowering costs, and improving responsiveness under heavy demand.
By optimizing orchestration around the model and intelligently routing requests across interconnected NVIDIA Hopper clusters, the platform eliminated redundant computation, a primary cost driver for long-context AI workloads. The result was sustained throughput, significantly faster time-to-first-token, and materially improved price-performance under high concurrency.
“As AI adoption accelerates, inference at scale is becoming the defining challenge for the industry,” said Dave Salvator, Director of Accelerated Computing Solutions at NVIDIA. “The integration of the NVIDIA accelerated computing platform with DigitalOcean’s inference-optimized platform unlocks the full potential of production-scale AI. The significant performance gains achieved by Workato highlight the impact of this collaboration.”
For AI companies scaling production, inference economics directly impact margins, making cost efficiency and predictability critical. By moving to DigitalOcean’s optimized environment, Workato reduced inference costs by 67% to $0.77 per million tokens while achieving a 33% hardware price-performance advantage.
Equally important, DigitalOcean’s managed Kubernetes environment abstracted control-plane complexity and GPU scheduling, allowing Workato’s lean AI Labs team to focus on research and product development rather than infrastructure management. This vertically integrated approach, spanning hardware, orchestration, and networking, is critical to reduce operational overhead while improving performance consistency and cost predictability.
“DigitalOcean lets us focus on research and advancing our models instead of managing infrastructure,” said Kevin Huang, Infrastructure Engineer at Workato AI Labs. “We can provision GPUs quickly, deploy inference workloads in production, and iterate on real customer traffic without getting bogged down in platform complexity. The speed and performance has been critical to maintaining our momentum.”
“Workato is pushing the frontier of agentic enterprise software,” said Paddy Srinivasan, CEO of DigitalOcean. “As AI companies move from experimentation into production, the winners will be those who can iterate quickly on real customer workloads. We’re proud to support Workato’s momentum by providing an inference-optimized environment that lets their team focus on shipping — not managing infrastructure.”
DigitalOcean is building the Agentic Inference Cloud for production AI, partnering with ambitious AI-native companies and enabling them to operate inference reliably at scale with predictable economics. Learn more about the DigitalOcean Agentic Inference Cloud .
About DigitalOcean
DigitalOcean is the Agentic Inference Cloud built for AI-native and Digital-native enterprises scaling production workloads. The platform combines production-ready GPU infrastructure with a full-stack cloud to deliver operational simplicity and predictable economics at scale. By integrating inference capabilities with core cloud services, DigitalOcean’s Agentic Inference Cloud enables customers to expand as they grow — driving durable, compounding usage over time. More than 640,000 customers trust DigitalOcean to power their cloud and AI infrastructure. To learn more, visit www.digitalocean.com .
View source version on businesswire.com: https://www.businesswire.com/news/home/20260303412463/en/
Media Relations
Meghan Grady: press@digitalocean.com
Investor Relations
Melanie Strate: investors@digitalocean.com
FAQ**
How do the recent performance improvements achieved by Workato's AI Research Lab on DigitalOcean's Agentic Inference Cloud, as reported, position DigitalOcean Holdings Inc. (DOCN) in the competitive landscape of AI infrastructure providers?
What specific strategies has DigitalOcean Holdings Inc. (DOCN) employed to enhance the cost efficiency and performance metrics of their platform, particularly for enterprise AI applications like those of Workato?
Considering Workato's substantial operational gains through DigitalOcean Holdings Inc. (DOCN), how could similar partnerships influence the future growth and market share of DigitalOcean in the AI industry?
What insights can investors glean from the collaboration between Workato and DigitalOcean Holdings Inc. (DOCN) regarding the scalability and profitability of AI-centric infrastructure solutions?
**MWN-AI FAQ is based on asking OpenAI questions about DigitalOcean Holdings Inc. (NYSE: DOCN).
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