VAST Data and Microsoft are deepening their alignment around next-generation AI infrastructure, announcing a new collaboration that will bring the VAST Data AI Operating System (AI OS) natively to Microsoft Azure. Unveiled at Microsoft Ignite, the partnership positions VAST Data as a strategic technology layer supporting what both companies describe as the coming wave of agentic AI.
These AI systems composed of autonomous, continuously reasoning software agents operate on massive, real-time datasets.
For Azure customers, the integration means they will be able to deploy VAST’s full data platform directly within the Microsoft cloud, using the same governance, security, operational tooling, and billing frameworks that define Azure-native services. The VAST AI OS, long known in enterprise AI circles for its performance-oriented architecture and unified data model, will now be available as a cloud service, simplifying deployment for organizations scaling AI workloads across on-premises, hybrid, and multi-cloud environments.
The partnership gives enterprises access to VAST’s unified storage, data cataloging, and database services, designed to support increasingly complex AI pipelines that incorporate vector search, retrieval-augmented generation (RAG), model training, inference, and real-time agentic processing. VAST’s architecture will run on Azure infrastructure, including the new Laos VM Series and Azure Boost accelerated networking, which are optimized for high-bandwidth AI workloads.
Jeff Denworth, co-founder of VAST Data, described the partnership as an inflection point for enterprise AI deployment. “Performance, scale, and simplicity are converging,” he said. “Azure customers will be able to unify their data and AI pipelines across environments with the same power, simplicity, and performance they expect from VAST – now combined with the elasticity and geographic reach of Microsoft’s cloud.”
Microsoft, for its part, sees the integration as a way to streamline the data and storage foundations required for the fast-growing segment of AI model builders working within Azure. “Many of the world’s leading AI developers leverage VAST for its scalability and breakthrough performance,” said Aung Oo, Vice President of Azure Storage. “Running VAST’s AI OS on Azure will help customers accelerate time-to-insight while reducing operational and cost barriers.”
At the center of the offering is a platform designed for agentic AI. VAST’s InsightEngine provides stateless compute and database services optimized for vector search, RAG pipelines, and high-performance data preparation. Its companion AgentEngine coordinates autonomous AI agents working across distributed environments, enabling continuous reasoning over data streams without requiring multi-step orchestration frameworks.
Azure CPU and GPU Clusters
From an infrastructure perspective, the VAST AI OS is engineered to maximize utilization of Azure CPU and GPU clusters. The platform integrates intelligent caching, metadata-aware I/O, and high-throughput data services to ensure predictable performance across training, fine-tuning, and inference cycles. This aligns with Microsoft’s broader strategy of building vertically integrated AI infrastructure – one that increasingly includes custom silicon investments.
A key differentiator of the VAST approach is its exabyte-scale DataSpace, which creates a unified global namespace across on-prem, co-lo, and cloud environments. The model gives enterprises the ability to burst GPU-intensive workloads into Azure without redesigning pipelines or migrating data – a capability that has traditionally slowed hybrid AI adoption.
VAST Data’s disaggregated, shared-everything (DASE) architecture extends into Azure as well, allowing compute and storage resources to scale independently. With built-in Similarity Reduction technology reducing the storage footprint of large AI datasets, the combined platforms aim to give customers both elasticity and cost containment – critical factors as model development increasingly demands multi-region, multi-petabyte environments.
The collaboration arrives as AI infrastructure requirements evolve rapidly. Autonomous agents, context-rich retrieval systems, and continuous-learning workflows require consistent performance across heterogeneous environments – something neither legacy storage architectures nor siloed cloud services were built to handle. By positioning VAST as a unified data substrate for Azure-based AI, Microsoft is betting on an architecture that can bridge those gaps at cloud scale.
Both companies say they will co-engineer future capabilities as Microsoft advances its next-generation compute programs. The long-term goal, they emphasize, is to ensure that regardless of model architecture or processor design, the underlying data layer can support AI workloads with predictability and scale.
Executive Insights FAQ
What does this partnership enable for Azure customers?
Azure users will be able to deploy the VAST AI Operating System natively in the cloud, giving them unified data services, high-performance storage, and AI-optimized compute pipelines without managing separate infrastructure.
How does the VAST AI OS support agentic AI?
VAST’s InsightEngine and AgentEngine allow organizations to run autonomous AI agents and stateful reasoning systems directly on real-time data streams, enabling continuous decision-making across hybrid and multi-cloud environments.
What advantages does the integration bring for AI model builders?
The platform keeps Azure GPU clusters fully utilized through high-throughput data services, intelligent caching, and metadata-optimized I/O – ensuring predictable performance for training, fine-tuning, and inference at scale.
How does VAST improve hybrid AI workflows?
Its global DataSpace functions as a unified namespace, allowing organizations to burst workloads into Azure without data migration or pipeline redesign, enabling seamless hybrid and multi-cloud operations.
How will the collaboration evolve as Microsoft introduces new AI hardware?
VAST Data and Microsoft will co-engineer future platform requirements so that emerging Azure infrastructure – including custom silicon initiatives – remains fully compatible with VAST’s AI OS, ensuring long-term scalability and performance.
