Bringing Real-Time AI Insights to Enterprise Data

VAST InsightEngine redefines enterprise AI with real-time data processing, unlimited linear scaling, secure AI-native vector search, and autonomous decision-making, enabling businesses to act instantly on dynamic data streams for faster, smarter insights.

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VAST replication expands up to 36 sites and now each one of the 32 different NHL arenas sends digital content to a single platform. We’ve set the table to create a content platform that exists at the edge, where the game is being played.

Derek Kennedy
NHL Vice President, Media Operations and DevOps, NHL
Power

Power Real-Time AI Decision-Making with Autonomous Agents

VAST InsightEngine eliminates the bottlenecks of traditional AI architectures, enabling real-time, event-driven AI decision-making. VAST DataEngine enables autonomous agents that can instantly process and act on live data, making it possible to automate fraud detection in financial services, deliver real-time cybersecurity response, power predictive maintenance in industrial automation, and enable automated content tagging in media. With real-time vector retrieval and event-driven inference, AI applications gain continuous access to the freshest data, optimizing accuracy and responsiveness without delays.

Streamline

Automate AI Data Pipelines for Seamless Workflows

VAST InsightEngine removes manual intervention from AI pipelines by leveraging event-driven triggers and functions, along with real-time inference automation. As soon as data is ingested, processing begins immediately—eliminating delays caused by batch-based ETL pipelines. AI-optimized search in VAST's integrated vector database then accelerates retrieval across petabyte- and exabyte-scale datasets, ensuring instant data access. By consolidating raw and vector storage, search, and inference into one AI-native platform, enterprises shift focus from managing infrastructure to extracting AI-powered insights at scale.

Real-Time

Transform Data into AI-Ready Insights—Instantly

VAST InsightEngine vectorizes enterprise data in real-time, eliminating traditional batch-based delays. AI-native vector embeddings make unstructured data instantly searchable in VAST's vector database, while retrieval-augmented generation (RAG) ensures AI models always reference the most current and relevant data. Memory-speed indexing removes search latency, allowing businesses to process vast datasets with trillions of vector embeddings, unlocking real-time semantic search at scale.

Scale

Unify and Secure AI Workflows—at Any Scale

VAST InsightEngine merges real-time storage, processing, and retrieval into a single, AI-native platform, eliminating the inefficiencies of siloed data architectures. AI pipelines remain fully encrypted, governed, and compliant with fine-grained access controls at the data element level, ensuring AI models only retrieve authorized information. VAST Data’s Disaggregated Shared-Everything (DASE) architecture scales effortlessly, enabling enterprises to process exabyte-scale AI workloads without infrastructure complexity. By removing data silos, redundant data copies, and third-party SaaS dependencies, VAST delivers a future-proof AI data foundation that is secure by design.

Simplify

Simplify AI Data Management with a Unified Architecture

Unlike traditional architectures that require complex integrations of multiple technologies to enable AI pipelines, like data lakes and third-party SaaS tools, VAST InsightEngine consolidates real-time storage, processing, vector store, and retrieval into a single, automated system. This eliminates the need for costly data copying, complex ETL pipelines, and integration-heavy workflows. Enterprises can now manage files, objects, tables, blocks, and streams in place, ensuring instant access to AI-ready data while reducing infrastructure overhead and accelerating time to insight.

Govern

Achieve Atomic Data Security and Compliance for AI

VAST InsightEngine ensures every AI data element is protected at the atomic level, with robust Access Control Lists (ACLs) and fine-grained access control, unified across raw and vector data. This eliminates the need to synchronize permissions across fragmented data systems manually, ensuring continuous security, compliance, and auditability. With built-in encryption, real-time monitoring, and AI-ready governance, enterprises can confidently deploy AI-driven workflows while maintaining full regulatory compliance and end-to-end data security.

Achieve Atomic Data Security and Compliance for AI

Generative AI with RAG capabilities has transformed how enterprises can use their data. Integrating NVIDIA NIM into VAST InsightEngine with NVIDIA helps enterprises more securely and efficiently access data at any scale to quickly convert it into actionable insights.

Justin Boitano
Vice President, Enterprise AI, NVIDIA
Features

Real-Time Data Processing

Data is immediately transformed into vector embeddings and graph relationships as it is written, bypassing traditional batch processing delays. This real-time processing ensures that newly ingested data is instantly available for AI operations, enabling faster, more accurate decision-making.

Scalable Vector Database

Designed to support trillions of vector embeddings, VAST's integrated, high-speed semantic database enables real-time similarity searches and relationships across large datasets. By leveraging Storage Class Memory (SCM) tiers and NVMe-oF, the platform scales seamlessly to accommodate growing enterprise data needs.

Unified Data Architecture

Consolidate data storage, processing, and retrieval into one integrated platform, reducing the need for external data lakes and SaaS tools. This architecture simplifies data management, cuts costs, and eliminates complex ETL processes, streamlining the entire AI workflow.

Data Governance and Security

Data updates are atomically synchronized across file systems, object storage, and the vector database. Built-in Access Control Lists (ACLs) ensure comprehensive security management and regulatory compliance across the data lifecycle, maintaining integrity and protection for AI operations, while fine-grained access control (FGAC) ensures only the right users and agents access the right data.

NVIDIA NIM Integration for Ingest and Retrieval

Leverages NVIDIA Inference Microservices to embed semantic meaning from incoming data in real time, and also for real-time inference and retrieval. Models running on NVIDIA GPUs instantly store embeddings in the VAST DataBase, enabling near-immediate availability for AI-driven tasks such as retrieval, eliminating processing delays and accelerating insights.

VAST Undivided Attention (VUA): Revolutionizing AI Inference

Infinite AI Cache, Unbounded Performance

VUA, an open-source global KV cache, extends GPU memory to shared NVMe. This offers AI models virtually limitless context, dramatically boosting inference speed, enhancing efficiency, and democratizing access to advanced caching for the entire AI community to accelerate innovation.

Scale AI Context Infinitely

VUA extends attention memory to shared EB scale NVMe flash, enabling AI models to handle massive contexts beyond GPU memory, reducing Time-To-First Token by up to 90%.

Smart Cache, Peak Efficiency

Intelligent prefix caching with partial context matching boosts hit rates and cuts redundancy, significantly saving precious GPU and CPU memory resources in demanding AI workloads like RAG.

Open Cache, Global Access

VUA’s open-source, globally shared architecture empowers the AI community by providing every GPU server access to an extended KV cache, enhancing load balancing and accessibility.

Infinite AI Cache, Unbounded Performance

VUA, an open-source global KV cache, extends GPU memory to shared NVMe. This offers AI models virtually limitless context, dramatically boosting inference speed, enhancing efficiency, and democratizing access to advanced caching for the entire AI community to accelerate innovation.

Scale AI Context Infinitely

VUA extends attention memory to shared EB scale NVMe flash, enabling AI models to handle massive contexts beyond GPU memory, reducing Time-To-First Token by up to 90%.

Smart Cache, Peak Efficiency

Intelligent prefix caching with partial context matching boosts hit rates and cuts redundancy, significantly saving precious GPU and CPU memory resources in demanding AI workloads like RAG.

Open Cache, Global Access

VUA’s open-source, globally shared architecture empowers the AI community by providing every GPU server access to an extended KV cache, enhancing load balancing and accessibility.