Persistent Systems, a leader in digital engineering, teamed up with DigitalOcean, a major cloud provider. They announced a multi-year partnership. This partnership seeks to simplify Artificial Intelligence. It also aims to make it more scalable and safer for businesses and developers worldwide. The collaboration shows that the industry is focused on making AI easier to adopt. This includes reducing costs, simplifying infrastructure, enhancing security, and scaling operations.
Under this agreement, Persistent has chosen DigitalOcean Gradient AI Agentic Cloud as the exclusive cloud and AI infrastructure provider for the SASVA platform-powered by AI that integrates code, documentation, enterprise architecture artifacts, and executive summaries to simplify workflows across development, operations, and business functions. SASVA will utilize DigitalOcean’s Gradient AI Platform, powered by GPUs, for compute-intensive development and inference loads of agents to reliably run AI applications in a cost-efficient manner.
The collaboration puts a several big pain points squarely in its crosshairs as AI adoption matures: an uptick in general GPU and infrastructure costs, fragmented AI agent ecosystems, and growing security and compliance concerns. By melding together the deep engineering and AI platform experience of Persistent with DigitalOcean’s agentic cloud infrastructure, the partnership hopes it can democratize enterprise-ready, scalable AI solutions.
Why This Partnership Matters to the AI Industry
Lowering Barriers to AI Adoption
A major barrier to using AI in businesses is the high cost and complexity of the infrastructure. High-performance GPUs and scalable platforms are often too expensive for mid-sized businesses. This pushes them into complicated or fragmented systems. Persistent and DigitalOcean’s partnership cuts AI infrastructure and operational costs by over 50%. This makes it easier for organizations of any size to run production-level AI workloads.
This would save costs and help more companies adopt AI. It would especially benefit those in regulated fields like finance, healthcare, and manufacturing. They could use AI more confidently and securely.
Focus on Security & Enterprise Readiness
As AI makes its journey from experiment to core business applications, security and compliance have become very important. Misconfigured AI systems, data leaks, and deployments of agents without protection are real risks. DigitalOcean’s agentic cloud, designed for secure and scalable AI hosting, together with Persistent‘s enterprise engineering experience, is positioned to give organizations the confidence to deeply embed AI into core operations without compromise on safety or compliance.
This focus on enterprise-grade AI is a big change from early tools. Those tools mainly prioritized performance and often overlooked governance and control. Businesses want more accountability and auditability. This partnership shows how platforms and services must change.
Expanding the Gradient AI Ecosystem
DigitalOcean’s Gradient AI already supports a suite of tools and integrations that run the gamut from GPU compute to full agentic workflows, diverse model catalogs, and infrastructure scaling in pursuit of making AI development and deployment easier. Partnerships like this grow the ecosystem. They help developers and businesses create strong, dependable AI apps. This way, they don’t need to piece together different services and cloud platforms.
This is symbolic of the bigger AI industry’s move towards integrated, managed, and predictable AI platforms rather than bespoke DIY stacks.
DevOps Implications: Simplifying AI Deployment & Operations
New Paradigm for DevOps Workflows
AI adoption, in particular at scale, makes significant demands on a DevOps team. CI/CD pipelines, infrastructure provisioning, monitoring, and cost management are all more complex when AI models and agents are involved.
This partnership does simplify the DevOps workflow on account of:
Offering ready-to-use managed environments for model training, deployment, and inference means less need for custom infrastructure management.
Also Read: AWS Moves to Speed AI Model Development, Introduces Checkpointless Training on SageMaker HyperPod
It offers predictable economics and clear pricing to help DevOps teams plan better.
Supporting seamless scaling as workloads grow, enabling teams to focus more on delivering features and less on maintaining infrastructure.
The operational burden usually accompanying AI workloads-versioning model artifacts, monitoring of inference performance, and automation of retraining workflows-is reduced by unified platforms such as DigitalOcean Gradient with Persistent’s SASVA.
Acceleration of AI-Powered DevOps Workflows
AI is increasingly used within DevOps itself-from automating test case generation and anomaly detection to optimizing deployment strategies based on historical performance. By embedding AI infrastructure directly into standard DevOps pipelines through a managed cloud platform, teams can:
Start using AI tools in automated test suites right now.
Monitor and respond to anomalies in production by using AI agents.
Employ AI-augmented observability tools to surface insights faster and reduce MTTR.
This accelerates the move toward AI-augmented DevOps-where developers and operations specialists use intelligent automation to boost velocity and reliability.
Business Implications in all Industries
Enterprises & Digital Native Companies
This will enable companies to scale from experimentation to production with lower technical risk and reduced costs. Enterprise customers, especially those bound by prior budgets in legacy infrastructure, will be better positioned to embed AI into the strategic workflow like customer support, fraud detection, code automation, and operational analytics.
SaaS and Platform Providers
Software and platform businesses can partner to deliver AI-enabled products faster. They can leverage Persistent’s engineering skills and DigitalOcean’s infrastructure. This collaboration helps create competitive, scalable solutions with strong integrations into customer systems.
Start-ups & AI Innovators
Startups and AI-native firms now have easy access to affordable AI infrastructure. They don’t have to negotiate with big cloud providers or spend on expensive GPU clusters. This level of accessibility sparks innovation. It opens doors to ideas that were once limited by budget or complexity.
Regulated & Security-Sensitive Sectors
With a managed cloud putting enterprise readiness and secure deployment practices first, healthcare, finance, and government clients/users-most of whom consider security and compliance the lifeblood of their operations-can adopt AI without risk and increase trust in AI operations.
Challenges & Considerations
Skill Gap: While the infrastructure gets easier, the teams still require expertise in prompt engineering, model governance, and secure AI lifecycle management. Security Governance – With secure platforms, AI workloads are in pressing need of strong governance policies, especially in regulated industries with data residency or compliance requirements.
Conclusion
The coming together of Persistent and DigitalOcean puts into motion a tectonic shift in the industry-from fragmented, expensive, and complicated AI adoption models to an enterprise-friendly, scalable, secure cloud infrastructure that assists organizations at all levels of maturity. It is going to accelerate this further by easing DevOps challenges, decreasing costs, and reducing technical barriers faster and farther than ever, making AI an integral part of enterprise operations and strategic innovation.
It shows the value of ecosystem collaboration for the AI industry; it simplifies the path for DevOps from experimentation to enterprise-grade AI deployment. And to businesses, regardless of size, it offers a path to taming AI with more predictability, security, and efficiency toward real-world business impact.