VAST Data

Beth Kindig

@Beth_Kindig

Nvidia-backed startup Vast Data has signed a $1.17 billion agreement with CoreWeave $CRWV, extending an existing partnership with Vast serving as the primary data foundation for CoreWeave’s AI cloud infrastructure. $NVDA

Chubby♨️

@kimmonismus

The Hidden Bottleneck in AI Factories: Data Infrastructure with Sven Breuner, VAST Data Everyone talks about GPUs. But in real-world AI infrastructure, the bottleneck is often somewhere else: the data layer. In this episode, I speak with Sven Breuner from VAST Data about the infrastructure behind modern AI systems - from GPU utilization and storage architecture to HPC, inference, data movement, and the emerging concept of AI factories. As companies invest billions into GPUs, many are discovering that compute alone is not enough. If data cannot move fast enough, GPUs sit idle, training becomes inefficient, and inference systems struggle to scale. In this conversation, we discuss: • Why GPUs often wait for data • How AI workloads differ from traditional HPC workloads • What happens when storage, metadata, and networking become bottlenecks • Why the data layer matters for both training and inference • What VAST means by an “AI Operating System” • How enterprises should think about infrastructure before buying more GPUs • Why the next generation of AI factories will require more than faster chips This is a deep dive into one of the most important but least understood parts of the AI stack: the infrastructure that makes large-scale intelligence possible. YouTube: https://t.co/IBqcvND6D1

Shay Boloor

@StockSavvyShay

$SMCI and VAST Data launched a joint enterprise AI platform with $NVDA to simplify and accelerate "AI factory" deployments. Jensen’s been saying the unit of sale is shifting from GPUs to racks to data centers https://t.co/8d4q41w83v

Mike

@MikeLongTerm

VAST Data Expands $AMD Partnership To Improve AI Inference Infrastructure 🧐🆕 So many new deals signed. VAST Data is a major private AI infrastructure company, valued at $30 billion (as of its April 2026 Series F), with roughly 1,000–1,200 employees. Shifting from pure training to inference and agentic AI. Inference (especially long-context, multi-turn agents) is increasingly a data/memory problem rather than pure compute. KV (key-value) cache which stores prior context so the model doesn’t recompute it, grows large and can bottleneck GPU HBM. VAST reports early tests with an @AMD Instinct MI355X showing ~9× faster time-to-first-token and ~9.7× higher token throughput under high-concurrency agentic workloads when offloading the cache. These results come from VAST and depend on configuration/workload. The partnership also includes automated cache expiration/deletion for data-lifecycle/compliance needs. VAST Data has expanded its collaboration with AMD to help cloud providers and enterprises build infrastructure for AI training, inference and agentic AI applications. The partnership combines the VAST AI Operating System with sixth-generation AMD EPYC processors, AMD Instinct graphics processors and AMD Pensando networking technology. The companies are addressing the growing infrastructure requirements created by AI agents, reasoning models and large-scale inference services. AI inference occurs when a trained model processes new information and generates a response or prediction. As organizations deploy agents with longer conversations and more persistent context, performance increasingly depends on managing data, memory and processor resources efficiently. VAST’s Disaggregated Shared Everything architecture provides unified access to storage, databases, streaming data and AI services across distributed environments. The expanded collaboration includes the use of sixth-generation AMD EPYC processors in VAST’s next-generation CBox and EBox platforms. VAST, AMD and DriveNets have also developed an AI infrastructure reference architecture combining AMD Helios rack-scale systems, the VAST AI Operating System and DriveNets networking. The architecture supports training, inference, reinforcement learning and key-value cache workloads. A key-value cache stores information previously processed by an AI model, allowing the system to reuse context rather than recomputing it for every request. VAST said early testing with an AMD Instinct MI355X processor produced a ninefold improvement in time to first token and 9.7 times higher token throughput when offloading the cache to VAST infrastructure during high-concurrency agentic workloads. The results were supplied by VAST and were not independently verified by AMD. Actual performance may vary depending on hardware and workload configuration. The collaboration also provides automated expiration and deletion of cached information that may contain personal or sensitive data. KEY QUOTES: “The industry is discovering that inference is fundamentally a data problem. Success depends on how effectively organizations can bring data, compute, memory and intelligence together as a single system.” John Mao, Vice President of Global Technology Alliances at VAST Data “Our expanded collaboration with VAST combines AMD EPYC CPUs and Instinct GPUs with the software foundation customers need to accelerate inference, improve infrastructure efficiency and deploy AI at scale.” Derek Dicker, Corporate Vice President of the Enterprise Business Group at AMD

Anp🅰️nman

@spacanpanman

$SHAZ: Sharon AI Expands Partnership with VAST Data to Power AI Factories Across Australia and Asia-Pacific Sharon AI to deploy 600PB of the VAST AI Operating System as the data foundation for its AI cloud infrastructure NEW YORK--(BUSINESS WIRE)--SharonAI Holdings Inc. (NASDAQ: SHAZ), a leading Australian Neocloud, and VAST Data, the AI Operating System company, today announced an expanded strategic partnership under which Sharon AI will deploy 600PB of the VAST AI Operating System across its AI cloud infrastructure. ShareUsing a proven benchmark of approximately 6PB of optimized AI storage per 1,000 GPUs for demanding large-scale workloads, the new 600PB VAST deployment provides the scalable data backbone equivalent to supporting the data needs of ~100,000 GPUs. The commitment makes the VAST AI Operating System the foundational data layer for Sharon AI's sovereign AI infrastructure, serving government, enterprise, research, and AI-native customers across Australia and Asia-Pacific. This deployment represents one of the largest and most advanced sovereign AI data foundations in the Asia-Pacific region. It positions Sharon AI at the forefront of Australia’s push to build independent, high-performance AI capability – keeping the nation’s most sensitive workloads, intellectual property, and strategic data firmly onshore while delivering the raw power needed for next-generation training, inference, and agentic AI systems. Using a proven benchmark of approximately 6PB of optimized AI storage per 1,000 GPUs for demanding large-scale workloads, the new 600PB VAST deployment provides the scalable data backbone equivalent to supporting the data needs of ~100,000 GPUs. This is a transformative leap that cements Sharon AI’s AI Cloud platform as one of the most substantial sovereign AI clouds in Australia and Asia-Pacific. For sovereign and regulated environments, control over data location, movement, and access is non-negotiable – and performance cannot be sacrificed. The VAST AI OS was engineered precisely for this challenge. Its breakthrough DASE architecture creates a true parallel distributed system that eliminates traditional bottlenecks. A single global namespace means every processor can reach all data instantly, without copying or moving petabytes around. Built-in multi-tenancy delivers strong isolation, guaranteed performance SLAs, and separate controls per customer – ideal for a cloud provider serving multiple sovereign tenants on shared infrastructure. The companies will continue close engineering collaboration to optimize the platform as Sharon AI’s customer workloads and AI factory ambitions scale rapidly. “Our customers refuse to choose between keeping their data sovereign and running AI at full speed – they need both at the highest level,” said James Manning, Co-Founder and CEO of Sharon AI. “Standardizing on the VAST AI Operating System at this unprecedented 600PB scale gives us exactly that: a rock-solid, high-performance foundation we can scale confidently as demand for sovereign AI across Australia and Asia-Pacific accelerates. This is how we build Australia’s AI future – powerful, secure, and proudly local.” “Every breakthrough Sharon AI enables – in research, medicine, industry, or national capability – runs on data, and it only moves as fast and safely as the foundation beneath it,” said Renen Hallak, Founder and CEO of VAST Data. “As the data foundation for Sharon AI’s sovereign cloud, we are proud to partner with them to support Australia’s hardest and most strategic AI ambitions. The VAST AI OS turns massive data estates into real-time intelligence assets, all while respecting sovereign boundaries. This is the future of AI infrastructure.” Full PR: https://t.co/aytuvFeAqP

Hunter Leath

@jhleath

if agents *really* start using the internet, then it stands to reason that there will be lots more internet traffic if there's lots more internet traffic, then the average website is going to have much more load, approaching the load of what the largest tech companies have today if every website has the load of ~facebook, then everyone will need to be able to serve ~facebook-scale traffic without having their own platform engineering team if everyone has ~facebook scale and doesn't have a 1,000 person platform org, what's the data infrastructure that's simple enough to deliver on that scale? is it still going to be specialized, expensive, single-tenant solutions like Pure storage or VAST data? probably not the world probably needs a simple, multi-tenant version of these services that delivers massive performance and scale for agents, databases, and websites that's where you'll find me

Jeff Denworth

Co-founder & CMO

Former CTERA executive and co-founder leading VAST Data's marketing and developer evangelism.

Jamie Filton

Director, Talent Acquisition

Previously at Nimble Talent · New York, New York, United States

Joined Jun 2026

Rakshith Venkatesh

Director of Product Management

Previously at MinIO · Fremont, California, United States

Joined Jun 2026

Ryan C.

Regional Director

Previously at Andromeda Security · Colorado Springs, Colorado, United States

Joined May 2026

Megan Roeske

Director NVIDIA Alliance

Previously at Deloitte · San Diego County, California, United States

Joined May 2026

Previously at Pacific Defense · Newark, California, United States

Joined Jun 2026

Previously at dbt Labs · Tokyo, Tokyo, Japan

Joined May 2026