Latest news with #InsightEngine
CNBC
10-06-2025
- Business
- CNBC
40. VAST Data
Founders: Renen Hallak (CEO), Jeff Denworth, Shachar Fienblit, Alon HorevLaunched: 2016Headquarters: New York CityFunding: $381 millionValuation: $9.1 billionKey Technologies: Artificial intelligence, deep neural networks/deep learning, explainable AI, generative AI, machine learningIndustry: Enterprise technologyPrevious appearances on Disruptor 50 list: 0 Software company VAST Data has an ambitious goal: It wants to redefine the data infrastructure stack for generative AI from the ground up. The company has rapidly become a disruptive force in enterprise storage and data computing, evolving from a startup with a flash storage concept into a full-fledged platform. In April, VAST Data platform was expanded to be fully integrated into Google Cloud, which allows customers to tap into its training, retrieval-augmented generation (RAG), inference, and analytics capabilities, allowing users to better access, move, manage and protect structured and unstructured data. "This collaboration represents a leap forward for organizations pushing the boundaries of what's possible with AI," VAST Data founder and CEO Renen Hallak said in a release. This is just one of a number of partnerships with major tech players. VAST released InsightEngine, a real-time AI retrieval application it developed with Nvidia. The app makes data instantly searchable and actionable for AI-driven applications and uses Nvidia's NIM microservices. "By unifying all elements of the AI retrieval pipeline into an enterprise data foundation, VAST Data InsightEngine with Nvidia is the industry's first solution to provide a universal view into all of an enterprise's structured and unstructured data to achieve advanced AI-enabled decision-making," VAST Data co-founder Jeff Denworth said in a release. VAST unites data management on its platform as an AI infrastructure enabler, which lets companies increase their data inputs and computation-intensive workloads. The company, which currently holds 50 patents, focuses on three types of businesses: high-performance computing including research institutions, AI cloud/model builders, and enterprise. Users include Cisco, Equinix, Supermicro and ServiceNow. It is also the data platform behind Elon Musk's xAI's Colossus cluster, the largest massive AI supercomputer in the world, located in Memphis, Tenn. Because its system can be used for the entire AI data lifecycle, it also opens it up to many competitors. Storage vendors like Pure Storage and Dell EMC offer similar services, in addition to data lakehouse and data fabric providers such as Snowflake and fellow Disruptor Databricks. Still, the company is bullish on the need for AI in the future. As of 2024, 78% of companies said they used AI in at least one functionality in their business, according to McKinsey. To further optimize growth, VAST has added Amy Shapero as its first CFO, who previously scaled Shopify's revenue from $700 million to $6 billion in just five years.
TECHx
04-06-2025
- Business
- TECHx
VAST Data Expands AI Partnership with Cisco
Home » Emerging technologies » Artificial Intelligence » VAST Data Expands AI Partnership With Cisco VAST Data, the AI Operating System company, has announced the expansion of its strategic partnership with Cisco. The collaboration aims to deliver a fully integrated and validated AI infrastructure stack. This stack spans compute, networking, storage, and observability. The VAST AI Operating System is now available directly through Cisco's Global Price List (GPL). It is also fully supported by Cisco as part of the joint solution. This move simplifies how enterprises implement, operate, and scale modern AI environments. As a result, customers can seamlessly procure and deploy the VAST AI OS alongside Cisco UCS servers, Nexus switching, and Cisco Nexus Hyperfabric AI. According to the companies, the joint offering supports the creation of enterprise AI Factories. These are agentic, data-intensive AI systems built for scale. The platform ensures security, performance, and operational agility from edge to core to cloud. Moreover, the solution enables customers to unify data pipelines and automate infrastructure management. It also supports real-time reasoning with scalable, zero-trust AI infrastructure. VAST Founder and CEO Renen Hallak will join Cisco President and Chief Product Officer Jeetu Patel at Cisco Live's Executive Symposium. They will host a fireside chat discussing the expanded partnership. The session will explore trends in enterprise AI adoption and future developments in AI-driven business. Jeremy Foster, SVP and GM of Cisco Compute, said the goal is to collapse complexity and deliver faster time-to-value. He stated that the companies aim to provide a unified infrastructure stack tailored for AI demands. The joint solution includes several integrated technologies: A consolidated AI stack combining Cisco's compute and networking with the VAST AI OS InsightEngine and AgentEngine for running AI pipelines, vector search, and real-time reasoning The companies reported that InsightEngine accelerates vector search, data preparation, and inference at the data point. AgentEngine extends this by orchestrating autonomous agents on live data streams. This enables real-time, event-driven decisions. They also revealed that the unified software stack simplifies infrastructure by managing structured, unstructured, and vector data together. This setup powers real-time reasoning and workflow automation at scale. The solution offers enterprise-grade performance with Cisco UCS compute and scalable Cisco Nexus network fabrics. These have been validated for seamless operation with VAST's Disaggregated Shared Everything (DASE) architecture. Cisco and VAST further reported that turnkey automation is achieved through SaaS-based orchestration via Cisco Nexus Hyperfabric AI. This works with VAST's intelligent dataflows and global namespace to streamline provisioning and scaling. Built-in security and multi-tenant readiness are also included. The infrastructure features zero-trust models, data governance, and platform security for sensitive AI workloads across hybrid and on-prem deployments. The VAST + Cisco solution is designed for generative and agentic AI workloads. It supports complex, data-driven applications with the insight and control needed for business transformation. Renen Hallak stated that this collaboration creates a foundational blueprint for enterprise AI. He added that aligning the VAST AI OS with Cisco's UCS and Nexus infrastructure delivers the simplicity, observability, and scalability enterprises need for global AI system management.
Channel Post MEA
02-05-2025
- Business
- Channel Post MEA
VAST Data Expands Collaboration With Google Cloud
VAST Data has announced an expanded collaboration with Google Cloud to help global enterprises and AI pioneers unlock the full potential of the VAST Data Platform. The VAST Data Platform, purpose-built for AI and large-scale data processing, is fully integrated into Google Cloud – offering a unified foundation for training, retrieval-augmented generation (RAG), inference, and analytics pipelines that span across cloud, edge, and on-premises environments. This tight integration enables capabilities and efficiencies not found in conventional architectures. The announcement follows a series of insightful conversations that VAST Data held at Google Cloud Next with enterprises and cloud leaders, focused on the future of intelligent infrastructure and the growing demand for unified, scalable data platforms. As the scale and complexity of AI workloads increase, organizations face mounting challenges around managing and moving data across disparate environments. The VAST Data Platform meets these challenges with a global, AI-native architecture that eliminates silos, simplifies operations, and delivers consistent performance across every stage of the AI lifecycle. VAST is advancing a new blueprint for enterprise AI – one that's open, hybrid, and built to scale. Key innovations now available as part of the VAST Data Platform on Google Cloud include: VAST InsightEngine for Intelligent Data Computation – The groundbreaking VAST InsightEngine brings stateless, high-performance database and compute services directly into the data platform. InsightEngine enables developers and researchers to run data-centric AI pipelines—such as RAG, preprocessing, and indexing—natively at the data layer, dramatically accelerating time-to-insight and reducing infrastructure complexity. The groundbreaking VAST InsightEngine brings stateless, high-performance database and compute services directly into the data platform. InsightEngine enables developers and researchers to run data-centric AI pipelines—such as RAG, preprocessing, and indexing—natively at the data layer, dramatically accelerating time-to-insight and reducing infrastructure complexity. Exabyte-Scale Global Namespace – The VAST DataSpace provides a single, unified global namespace for all applications and services, eliminating data silos typically found in hybrid and multicloud environments by connecting data on-premises, at the edge, and in Google Cloud as well as other hyperscalers for seamless data access and mobility. – The VAST DataSpace provides a single, unified global namespace for all applications and services, eliminating data silos typically found in hybrid and multicloud environments by connecting data on-premises, at the edge, and in Google Cloud as well as other hyperscalers for seamless data access and mobility. Unified File, Object, Block and Database Access – The VAST Data Platform is the only solution that brings file (NFS, SMB), object (S3), block, and DataBase services into one globally coherent system. This architecture provides unprecedented flexibility for data teams to build, analyze, and train AI models—all from a single platform. The VAST Data Platform is the only solution that brings file (NFS, SMB), object (S3), block, and DataBase services into one globally coherent system. This architecture provides unprecedented flexibility for data teams to build, analyze, and train AI models—all from a single platform. Optimized for Mixed I/O and Metadata-Intensive Workloads – The VAST Data Platform is optimized for modern AI workflows, handling random access patterns, small files, and metadata-heavy operations with ease—ideal for neural search, model training, and inferencing at scale. The VAST Data Platform is optimized for modern AI workflows, handling random access patterns, small files, and metadata-heavy operations with ease—ideal for neural search, model training, and inferencing at scale. Cost-Efficient Disaggregated, Shared-Everything Architecture – Ability to independently scale compute from the base storage platform for compute dense and high throughput workloads allows for elastic scalability and cost-efficiency, enabling independent scaling of performance and capacity. Additionally, VAST's unique Similarity Reduction is always-on and drastically cuts physical capacity needs to deliver substantial cost savings. 'This collaboration represents a leap forward for organizations pushing the boundaries of what's possible with AI,' said Renen Hallak, Founder & CEO of VAST Data. 'By combining the elasticity and reach of Google Cloud with the intelligence and simplicity of the VAST Data Platform, we're giving developers and researchers the tools they need to move faster, build smarter, and scale without limits.' The integration is available through Google Cloud enabling organizations to quickly deploy VAST's enterprise-grade platform to accelerate AI, ML, and analytics initiatives without operational overhead. Customers can now unify their AI training, RAG pipelines, high-throughput data processing, and unstructured data lakes on a single, high-performance platform – reducing complexity and unlocking new possibilities in data-driven innovation. 'Our collaboration with VAST Data brings together Google Cloud's powerful, flexible infrastructure with a unified data platform purpose-built for AI,' said Sameet Agarwal, VP/GM Storage, Google Cloud. 'VAST is enabling customers to simplify data operations and accelerate performance across their demanding, data-intensive AI workloads.' 0 0
