VAST Data, the AI data platform company, has announced an expanded collaboration with Google Cloud. The integration is designed to help global enterprises and AI pioneers fully harness the power of the VAST Data Platform. Purpose-built for AI and large-scale data processing, the VAST Data Platform is now tightly integrated into Google Cloud infrastructure.

This enhanced integration provides a unified foundation for AI workloads. It supports training, retrieval-augmented generation (RAG), inference, and analytics. These capabilities span cloud, edge, and on-premises environments. The platform’s architecture introduces efficiencies that conventional systems lack.

The announcement follows VAST’s presence at Google Cloud Next. During the event, the company engaged in discussions with enterprises and cloud leaders. The focus was on the future of intelligent infrastructure and the need for scalable, unified data platforms.

As AI workloads grow in size and complexity, many organizations face difficulties managing data across various environments. The VAST Data Platform solves this with an AI-native architecture. It eliminates data silos, simplifies operations, and ensures consistent performance across all stages of the AI lifecycle.

Key innovations now available as part of the VAST Data Platform on Google Cloud include:

• VAST InsightEngine: A stateless, high-performance compute and database layer built into the platform. It enables native execution of AI pipelines such as RAG, preprocessing, and indexing. This reduces infrastructure complexity and improves time-to-insight.
• Exabyte-Scale Global Namespace: The VAST DataSpace provides a unified global namespace. It connects data across on-premises, edge, and Google Cloud environments. This removes silos commonly found in hybrid and multicloud setups.
• Unified Data Access: The platform supports file (NFS, SMB), object (S3), block, and database services. All operate within one globally coherent system. This allows flexibility for building, training, and analyzing AI models.
• AI-Optimized Performance: It is tuned for workloads with random access patterns, small files, and metadata-intensive operations. This suits neural search, model training, and large-scale inferencing.
• Disaggregated, Cost-Efficient Architecture: Compute and storage scale independently. This supports compute-dense, high-throughput workloads while maintaining cost efficiency. VAST’s always-on Similarity Reduction further lowers physical storage needs.

Renen Hallak, Founder and CEO of VAST Data, said the collaboration marks a major step forward. “By combining the elasticity and reach of Google Cloud with the simplicity of the VAST Data Platform, we’re giving developers and researchers the ability to scale, build smarter, and innovate faster,” he said.

The integrated solution is available through Google Cloud. It enables fast deployment of VAST’s enterprise-grade platform. Organizations can now streamline AI training, RAG workflows, analytics, and unstructured data processing. All workloads can run on one high-performance platform, reducing complexity and driving innovation.

Sameet Agarwal, VP/GM of Storage at Google Cloud, said, “Our collaboration with VAST Data brings together flexible infrastructure with a unified AI data platform. Customers can now accelerate performance across demanding, data-intensive AI workloads.”

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