Partner POV | Unlocking Real-Time AI with VAST InsightEngine

Article written and provided by, VAST Data. 

AI innovation is accelerating across industries, but outdated data architectures continue to make it difficult to reach full potential. Traditional storage and analytics platforms rely on batch processing, creating delays that make real-time AI applications—such as fraud detection, predictive analytics, and generative AI—increasingly difficult to scale. As data volumes grow exponentially, organizations struggle with lack of real-time performance, high infrastructure costs, and complex integration requirements that hinder AI-driven decision-making. 

VAST InsightEngine eliminates these barriers by enabling real-time data capture, embedding, and retrieval—without the inefficiencies of legacy data architectures. By integrating AI-native vector search and retrieval-augmented generation (RAG) with a high-performance, scalable data infrastructure, InsightEngine allows organizations to optimize AI workloads at scale. 

Moving Beyond Batch AI to Real-Time Intelligence 

Batch data processing has long been a limitation for AI applications. Insights derived from outdated or incomplete datasets lead to suboptimal decision-making and missed opportunities. AI models that rely on scheduled data updates often fail to capture real-world changes in time to act. 

VAST InsightEngine provides an event-driven approach to AI data management, where new data is embedded and segmented, and available for retrieval—ensuring AI models operate with the most current, contextually relevant information. This shift from batch processing to real-time AI dramatically improves inference accuracy, allowing businesses to respond faster to market changes, security threats, and customer interactions. 

Scaling AI Without Performance Bottlenecks 

AI workloads demand infrastructure that can scale alongside rapidly growing datasets. Traditional architectures often struggle with performance degradation as data volumes increase. Long query times and high compute overhead result in costly inefficiencies that slow down AI-driven initiatives. 

VAST InsightEngine removes these scalability constraints with a disaggregated, shared-everything (DASE) architecture that eliminates the trade-offs between performance and capacity. AI-driven applications can now: 

• Run vectorized AI search and RAG pipelines on petabyte-scale datasets without slowdowns. 
• Query and retrieve AI-ready data instantly, ensuring models are always trained on the freshest information. 
• Scale seamlessly across multiple workloads while maintaining high-speed, low-latency performance. 

This approach maximizes GPU utilization, reducing the need for costly infrastructure expansion and making AI pipelines significantly more cost-efficient. 

A Secure and Compliant AI Data Pipeline 

Security and governance challenges continue to be a major concern for organizations deploying AI at scale. AI data pipelines are often vulnerable to unauthorized access, compliance risks, and evolving regulatory requirements—especially when dealing with sensitive information in industries like finance, healthcare, and government. 

VAST InsightEngine is built with enterprise-grade security and governance at every stage of the AI workflow. Data is protected through fine-grained access control, encryption, and real-time monitoring, ensuring compliance with industry regulations. With built-in zero-trust security and policy-based governance, organizations can confidently scale AI initiatives without exposing critical data to risk. 

AI-Optimized Efficiency with Lower Costs 

AI deployments often come with high operational costs due to inefficient data management, redundant storage layers, and consulting-heavy integrations. VAST InsightEngine reduces total cost of ownership (TCO) by eliminating the need for multiple data copies, streamlining data engineering, and simplifying the AI data pipeline. Search capabilities streamline AI workflows, reducing time-to-insight while optimizing infrastructure spend. 

By integrating real-time AI search, retrieval, and inference into a single, scalable platform, InsightEngine allows businesses to unlock the full potential of AI-driven decision-making—faster, smarter, and at a lower cost. 

WWT + VAST: Accelerating AI Deployment at Scale 

Before deploying AI at scale, organizations need a way to validate models, fine-tune performance, and ensure seamless integration with existing infrastructure. WWT's AI Proving Ground (APG) and Advanced Technology Center (ATC) provide an enterprise-scale environment to test AI workloads under real-world conditions. By integrating VAST InsightEngine, teams can: 

• Eliminate storage bottlenecks that slow down AI model benchmarking. 
• Run real-time vectorized AI search without costly cloud dependencies. 
• Ensure security and compliance across the entire AI data pipeline, from ingestion to inference. 

This collaboration enables enterprises to accelerate AI innovation and deployment, reducing time-to-insight and optimizing infrastructure efficiency—without the complexity of traditional AI data management approaches. 

The Future of AI is Real-Time 

As AI adoption continues to expand, real-time data processing is no longer optional—it's essential. VAST InsightEngine provides the foundation for high-performance, scalable, and secure AI that meets the demands of modern enterprises. By eliminating batch processing delays, removing scalability barriers, and ensuring AI-ready security and compliance, it enables organizations to move beyond the limitations of traditional architectures and accelerate AI innovation.