WEKA and Andromeda partner to power AI workloads at global scale. 30/07/2026 Partnership delivers consistent, high-performance AI storage across Andromeda's global provider network, lowering the total cost of innovation for AI teams CAMPBELL, Calif., July 30, 2026 /PRNewswire/ - WEKA, the AI data and memory infrastructure company, today announced that Andromeda, the platform connecting AI teams with high-performance compute, is integrating the WEKA NeuralMesh platform as a core AI data storage layer for managed GPU clusters. Andromeda's customers can now access a dedicated NeuralMesh or a GPU-native WEKA NeuralMesh Axon deployment to achieve consistent storage performance across any cluster running on any hyperscaler or AI cloud. WEKA and Andromeda: powering AI teams building at the frontier Keeping GPUs Fed Across Every Environment Andromeda is on a mission to make high-performance compute available to every team building at the frontier, so breakthroughs are driven by ideas, not hardware access. The company works with leading AI labs, data centers, and cloud providers, routing training and inference jobs across the global supply chain. Andromeda operates across more than 50 compute providers worldwide, routing training and inference workloads through a growing global fleet of managed clusters. Every cluster on Andromeda's platform must meet the same quality benchmarks regardless of who operates the infrastructure; the company certifies each cluster across GPU, storage, network fabric, and security before it reaches a customer. That standard exposed a hard problem: each provider brought its own storage environment and performance varied cluster to cluster. With WEKA, Andromeda achieves significant performance gains on existing hardware, deployment in minutes, consistency across every provider, and lower storage costs. "Our goal is to enable the global flow of compute, and that means every cluster we deliver has to perform, no matter where the capacity comes from. Standardizing on WEKA NeuralMesh has given our customers hyperscaler-grade consistency with open-market flexibility at the storage and memory layer, where performance is won or lost," said Wil Moushey, CEO at Andromeda. "Idle GPUs are throttling the pace of AI innovation. WEKA helps us ensure every GPU we manage is earning its keep." GPU-Native AI Storage & Memory, Deployed in Minutes When one research lab found its workloads bottlenecked by its cluster's supplied storage, Andromeda deployed NeuralMesh Axon on the same hardware, unlocking the performance the lab needed, without additional infrastructure. NeuralMesh Axon is the GPU-native deployment of the NeuralMesh software platform. It fuses storage directly into Andromeda's GPU servers, converting each cluster's existing NVMe into a unified, high-performance data layer that feeds training and inference at full speed. Because that infrastructure is already racked, powered, and paid for, it adds performance without adding footprint, power draw, or cost. Using the NeuralMesh Kubernetes Operator, Andromeda can stand up a complete NeuralMesh cluster in minutes and manage its full fleet through the same workflows that run every other layer of the stack. Among Andromeda's NeuralMesh deployments, roughly half run NeuralMesh Axon; the rest run dedicated NeuralMesh deployments for customers who need every GPU core and every gigabyte of memory dedicated to their workloads. Wherever it's deployed, NeuralMesh delivers the same performance floor, regardless of which provider's hardware sits underneath it. That reliability allows Andromeda to onboard customers onto clusters that previously had no shared storage. For Andromeda, the impact is evident: * Ready on day one. New NeuralMesh Axon clusters deploy in as little as 10 minutes, so AI teams start running workloads the day their cluster comes online. * Rapid iteration. AI teams building on Andromeda-managed clusters have seen environment startup load times drop from three minutes to 30 seconds, fitting more experiments into every day. * Performance at scale. Andromeda clusters running on NeuralMesh Axon are achieving sustained throughput of over 400 GB per second per cluster and over 6 million IOPS in production. That performance enabled one Andromeda biotech customer to complete metadata-heavy transfers involving one billion files per directory in minutes rather than hours. * Native resilience. When faults threaten to cascade across an Andromeda cluster, NeuralMesh contains them and keeps the cluster available, protecting every customer workload. "Andromeda's first WEKA NeuralMesh Axon deployment took just 10 minutes to stand up from bare metal. That became our blueprint," said Vishvajit Kher, lead architect at Andromeda. "If a cloud provider doesn't offer shared storage, we're no longer blocked. We deploy WEKA NeuralMesh and know it will perform. It's a full-featured system, up to 90% less expensive than market alternatives, delivering savings that compound as we scale. Every dollar flows straight through to benefit the AI teams we serve." "Andromeda is solving one of the hardest problems in AI infrastructure: making compute from more than 50 different providers feel like one platform," said Liran Zvibel, co-founder and CEO at WEKA. "WEKA NeuralMesh extends that promise to the data layer, deploying in minutes and feeding training and inference workloads at full speed on any GPU provider's hardware, anywhere in the world. The teams building on Andromeda can skip the storage question entirely and start innovating. Together, we're helping AI teams reduce time from idea to outcome." Extending to the Newest Generation of AI Infrastructure Andromeda is deploying WEKA NeuralMesh across its global platform, spanning dedicated and GPU-native deployments. The partnership is already extending to next-generation AI hardware as Andromeda scales its global platform. AI teams interested in running workloads on Andromeda can get started at andromeda.ai. About Andromeda Andromeda connects buyers and suppliers of compute through a single platform that makes AI infrastructure easier to buy, sell, and operate - combining the simplicity and reliability of a hyperscaler with the flexibility, speed, and economics of an open market. Buyers get one interface to a global network of compute providers, with reservations, on-demand, and spot capacity validated against consistent benchmarks. Suppliers get the software, expertise, and distribution to acquire customers, run GPU clusters, and monetize capacity at scale. Andromeda serves more than 100 AI customers across 50+ capacity providers, with billions of GPU-hours supported. Learn more at www.andromeda.ai. About WEKA WEKA is the AI data and memory infrastructure company transforming the economics of agentic AI. The WEKA(R) NeuralMesh(TM) platform extends high-performance data storage and GPU memory to wherever they need to run, giving enterprises, AI cloud providers, and AI builders a unified foundation for training, inference, and agentic workloads. With WEKA Augmented Memory Grid, NeuralMesh extends GPU memory capacity by 1000x, accelerating time to first token by up to 20x, and serving 10x more concurrent users from the same GPU footprint, proven in production benchmarks. Trusted by leading global enterprises, frontier labs, and AI cloud providers, WEKA empowers customers to maximize GPU utilization, generate more tokens per watt, lower their cost per token, and scale production AI faster. Learn more at www.weka.io, or connect on LinkedIn and X. WEKA, WEKApod, and the W logo are registered trademarks of WekaIO, Inc. Other trade names herein may be trademarks of their respective owners. WEKA, The Foundation for Enterprise & Agentic AI Innovation 02/07/2026 18/08/2014 13/05/2026 27/04/2026 30/04/2026

WEKA debuts NeuralMesh 6 for enterprise AI workloads. WEKA debuted NeuralMesh 6, redefining inference economics with native multi-tenancy and a unified file-and-object protocol stack built on NVMe, in what the company calls its most significant software release. CAMPBELL, Calif., July 22, 2026 /PRNewswire/ - WEKA, the AI data and memory infrastructure company, today announced WEKA NeuralMesh 6, the most significant software release in the company's history, delivering a purpose-built platform designed to help customers run production AI training, inference, and accelerated compute workloads at production scale on a single unified software stack. The release offers a robust set of capabilities that the AI infrastructure market has historically forced operators to assemble from separate vendors: native multi-tenancy at hyperscale, a full S3 protocol stack on NVMe, intelligent metadata-first data mobility that delivers async replication and remote caching, always-on data reduction with contractual guarantees, Kubernetes-native operations, and unified observability across every deployment. Inference Costs Now Decide Which AI Companies Scale The release arrives as the AI industry increasingly shifts decisively from training to production inference. Long-context reasoning, agentic workflows, and retrieval-driven AI workloads place sustained pressure on memory, metadata, and storage in ways traditional infrastructure architectures were not designed to handle. NeuralMesh 6 was built to deliver breakthrough inference economics at production scale for AI clouds, frontier model providers, government agencies, and large enterprises at the forefront of AI innovation. Inference Economics Proven in Production on Oracle Cloud Infrastructure NeuralMesh powers hyperscale AI inference in production today on Oracle Cloud Infrastructure (OCI). Leveraging WEKA's Augmented Memory Grid capability, which extends GPU memory by accelerating persistent KV cache access to NeuralMesh-managed NVMe storage, benchmarks on OCI H100 infrastructure have demonstrated 10x higher token throughput, 10x more concurrent users served, and 7x more tokens per GPU in production deployments. "As agentic AI workloads push context windows and GPU utilization to new limits, WEKA and Oracle Cloud Infrastructure are helping customers scale inference more efficiently without simply adding more GPUs," Pablo Selem, senior director, software development, Oracle Cloud Infrastructure. "WEKA's NeuralMesh platform with Augmented Memory Grid on OCI helps remove memory bottlenecks, delivering substantially more throughput and concurrent users from the same GPU footprint. For customers, that means higher ROI on infrastructure investments and a clearer path to cost-efficient AI at scale." Inside NeuralMesh 6 NeuralMesh 6 builds on this production foundation. Key features and capabilities include: Native Multi-Tenancy at Hyperscale NeuralMesh 6 delivers the industry's only multi-tenancy architecture that combines physical hardware isolation with logical network isolation on a single platform. * Composable Clusters provide complete hardware-level isolation, dedicated CPU, memory, and storage drives per tenant for anchor tenants that require guaranteed resources, workload separation, and predictable performance under load. * Virtual Multi-Tenancy provides VPC-like network isolation through WEKA's Virtualized RDMA Data Fabric (VRDF), supporting private VLANs, overlapping IP address spaces, per-tenant quality of service (QoS), per-tenant encryption with independent KMS, and independent LDAP/AD authentication. Virtual MT scales to more than 1,000 isolated logical tenants per cluster, with new tenant provisioning in under 30 minutes. The two tiers compose. A single WEKA hardware cluster running 50 Composable Clusters can support up to 50,000 logically isolated tenants on the same physical infrastructure - a path from dozens of tenants to tens of thousands without re-architecting. Full S3 Protocol Stack on NVMe NeuralMesh 6 delivers a fully-featured, native S3 implementation in which the same physical data blocks are addressable via S3 and POSIX simultaneously - not a gateway that translates between protocols, but a single unified namespace. A file written via NFS or POSIX is immediately readable via S3, and vice versa, eliminating the multiple full-dataset copies that a conventional AI pipeline carries between the training, fine-tuning, and inference stages. The implementation is built for AI workload patterns: 2,000 to 5,000 concurrent S3 connections per node, roughly five times the concurrency of conventional S3 architectures. S3 over RDMA enables zero-copy data transfer directly to GPU memory. Object storage is no longer a secondary tier - it is a high-performance protocol native to the same platform that serves POSIX file workloads. Intelligent Replication for AI Workloads GPU infrastructure is increasingly distributed across sites, clouds, and regions. Traditional replication architectures force organizations to wait for complete data copies before workloads can begin - a model that breaks down when GPU availability shifts in hours rather than weeks. NeuralMesh 6's intelligent replication changes the model. The same foundation supports AI data mobility, cloudbursting, and multi-site collaboration. Metadata-first replication makes destination environments immediately browsable. Data hydrates on demand, only when accessed, reducing WAN traffic and eliminating unnecessary full-dataset copies. Organizations can place workloads where GPU capacity exists today rather than where data was originally written. In this first step towards complete federation and a global namespace, NeuralMesh 6 unlocks async replication and instantaneous remote caching functionality. Always-On Data Reduction with Performance Guarantees NeuralMesh 6 introduces always-on data reduction, specifically designed for AI workloads, with fingerprinting, similarity hashing, deduplication, and compression. It delivers less than 5% write overhead, up to 6x capacity savings on AI training data, and a contractual guarantee of both the data reduction ratio and the performance impact. The performance tax that has historically forced operators to choose between efficiency and speed is gone: data reduction is on by default, every deployment, every workload. Customer-specific pre-sales analysis can project workload-based reduction outcomes before deployment. AlloyFlash Automated TLC + QLC Flash Tiering AlloyFlash enables combining TLC and QLC NVMe flash within a single cluster, transparently routing latency-sensitive operations to TLC while leveraging QLC at roughly 30-40% lower cost per terabyte for bulk-capacity workloads. AlloyFlash makes the highest-density WEKApod configurations production-viable, not just capacity-on-paper. Automatic, transparent, no customer configuration required. NeuralMesh Kubernetes Operator NeuralMesh Kubernetes Operator automates cluster deployment and lifecycle management in Kubernetes environments. For neo-clouds and AI research labs running Kubernetes as their operational standard, Kubernetes Operator reduces deployment time from weeks to hours and brings NeuralMesh into the same declarative operational model their compute infrastructure already uses. NeuralMesh Observe NeuralMesh Observe is SaaS-based observability built for high-performance AI storage. Unified multi-cluster dashboards, client-level diagnostics, intelligent alerting with configurable thresholds, and routing to Slack, PagerDuty, or email with direct links to relevant dashboards. Included with every NeuralMesh deployment at no additional cost. "WhiteFiber is building a distributed GPU platform across multiple data centers connected by high-speed dark fiber. At our scale, data mobility isn't a nice-to-have; it's foundational," said Sam Tabar, CEO at WhiteFiber. "NeuralMesh's intelligent replication makes data mobility real at scale: we can make datasets visible across sites and pull exactly the data each job needs to the next GPU allocation as it becomes available. That shifts replication from a back-end protection function to a core part of how our distributed AI infrastructure needs to operate, improving workload mobility, capacity efficiency, and the resiliency our customers depend on. WEKA's data and memory infrastructure provides the foundation to scale our footprint without compromise. We're excited to keep building on that together." "The infrastructure operators running production AI today have been forced to assemble platforms from vendors that were never designed to work together. Separate stacks for file and object, manual data movement between them, multi-tenancy bolted on after the fact. NeuralMesh 6 delivers what they've actually needed all along: a single platform that handles the high-performance file layer and the high-capacity object layer on the same blocks, with native multi-tenancy, intelligent data mobility, and always-on data efficiency built in from the start. This is what production inference infrastructure looks like when it's designed for the workload, not retrofitted for it," said Ajay Singh, Chief Product Officer at WEKA. Availability NeuralMesh 6 will be generally available in the second half of 2026. Existing WEKA customers can upgrade to NeuralMesh 6 at no additional cost through standard upgrade channels and should contact their Customer Success representative for more details. NeuralMesh x WEKApod: Built to Run In Perfect Symmetry Together WEKA also announced the third generation of WEKApod Nitro, WEKApod Prime, and WEKApod Prime Max, the first AI storage appliances built on WEKA-designed and engineered hardware to optimize its NeuralMesh software platform. The systems deliver 1.1 exabytes of effective capacity per rack with multiple patents pending. See today's WEKApod announcement to learn more: https://www.weka.io/news/wekapod-3-densest-ai-storage-memory-system.