The race to integrate artificial intelligence into enterprise operations is accelerating, with businesses seeking efficient ways to deploy AI-driven solutions at scale. In response, Oracle and NVIDIA have announced a new collaboration aimed at removing barriers to AI adoption, integrating NVIDIA’s accelerated computing and inference software with Oracle’s cloud infrastructure to support the rise of agentic AI applications.
This integration, which will see over 160 AI tools and 100 inference microservices made available through the Oracle Cloud Infrastructure (OCI) Console, marks a significant step towards simplifying AI deployment. With the rise of generative AI and autonomous decision-making models, enterprises face mounting challenges in infrastructure, data processing, and scalability. By leveraging OCI’s cloud capabilities alongside NVIDIA’s AI software stack, the partnership seeks to address these obstacles, providing organisations with the tools needed to rapidly implement AI applications while maintaining flexibility and security.
Accelerating AI deployment for enterprise transformation
AI’s transformative potential lies in its ability to streamline operations, automate processes, and generate valuable insights. Yet many enterprises struggle to implement AI efficiently due to technical complexity and fragmented infrastructure. Oracle’s partnership with NVIDIA aims to simplify this process through a native integration of NVIDIA AI Enterprise with OCI, offering an optimised AI stack that can be deployed in public clouds, private data centres, or at the edge.
Safra Catz, chief executive of Oracle, believes this collaboration will significantly lower the barriers to AI adoption. “Oracle has become the platform of choice for both AI training and inferencing, and this partnership enhances our ability to help customers achieve greater innovation and business results,” she said. Jensen Huang, founder and chief executive of NVIDIA, echoed this sentiment, highlighting the synergy between the companies. “Oracle and NVIDIA are perfect partners for the age of reasoning, helping enterprises innovate with agentic AI to deliver amazing things for their customers and partners.”
A structured approach to AI implementation
A core challenge of enterprise AI adoption is ensuring models are deployed effectively and at scale. Oracle’s AI Blueprints provide a structured approach to AI implementation, offering no-code deployment recipes to help businesses quickly run workloads without needing deep technical expertise. NVIDIA’s own AI Blueprints complement this by enabling organisations to build custom AI applications with minimal complexity, supporting use cases from customer service automation to real-time analytics.
Biotechnology firm Soley Therapeutics is among the enterprises leveraging this integration to accelerate AI-driven drug discovery. By combining OCI’s AI infrastructure with NVIDIA’s Blackwell GPUs and inference microservices, the company aims to decode cellular interactions to forecast cell fate, a process requiring vast computational power and storage capacity. Yeremi Yeghiazarians, co-founder and chief executive of Soley Therapeutics, sees the integration as a crucial enabler for innovation. “The combination of OCI and NVIDIA delivers a full-stack AI solution, providing us the storage, compute, software tools and support necessary to innovate faster with petabytes of data,” he said.
Bringing AI inference to real-time enterprise applications
The efficiency of AI applications depends not just on training but also on inference, the process of making predictions and generating insights from trained models in real time. The availability of NVIDIA’s NIM inference microservices within OCI Data Science enables businesses to deploy AI-powered assistants, real-time recommendation engines, and automation tools with minimal setup. Organisations can access these capabilities on a flexible, pay-as-you-go basis, ensuring AI remains both scalable and cost-effective.
Companies such as Pipefy, which automates business process management, have embraced this approach. Gabriel Custodio, principal software engineer at Pipefy, explained how AI Blueprints have enabled rapid model deployment. “Using these prepackaged and verified blueprints, deploying our AI models on OCI is now fully automated and significantly faster,” he said.
Vector search and the next generation of AI data management
Beyond AI inference, the partnership is driving advances in database technology. Oracle Database 23ai will incorporate NVIDIA’s cuVS library to accelerate AI-powered vector search, a technology increasingly crucial for recommendation systems, semantic search, and fraud detection. Vector search enables organisations to process and analyse large-scale unstructured data efficiently, unlocking new possibilities for AI-driven insights.
DeweyVision, a firm specialising in AI-powered media search, is already leveraging these capabilities. Majid Bemanian, chief executive of DeweyVision, highlighted the potential impact. “Oracle Database 23ai with AI Vector Search can significantly increase Dewey’s search performance while increasing the scalability of the DeweyVision platform,” he said. By integrating NVIDIA GPUs into its AI pipeline, the company aims to enhance its ability to process vast amounts of video and image data for real-time content discovery.
Scaling AI infrastructure for the future
Oracle and NVIDIA’s collaboration extends beyond software to encompass the AI infrastructure itself. OCI will be among the first cloud providers to offer the next generation of NVIDIA Blackwell accelerated computing, designed to support AI models requiring extreme scalability. With NVIDIA’s Quantum-2 InfiniBand networks and NVLink functionality, enterprises will be able to build high-performance AI superclusters capable of training and deploying large-scale models with unprecedented efficiency.
SoundHound, a leader in conversational AI, is already leveraging NVIDIA GPUs on OCI to power voice-related applications, processing billions of queries annually. As AI models grow in size and complexity, access to high-performance infrastructure will be essential for businesses looking to maintain a competitive edge.
The push to integrate AI into enterprise operations is no longer about whether businesses should adopt AI, but how they can do so efficiently and at scale. By addressing key challenges in deployment, infrastructure, and AI inference, Oracle and NVIDIA’s collaboration represents a significant milestone in enabling businesses to transition from AI experimentation to enterprise-wide implementation. The question now is not just how AI can transform industries, but how quickly organisations can embrace this shift to drive meaningful impact.
