Accelerate Design, Production, and Quality Across
Manufacturing Workflows
Across computer aided engineering (CAE), aerospace, automotive, robotics, and semiconductor fabrication workflows, NeuralMesh™ offers a high-performance data platform built for AI training, inference, and large-scale manufacturing workloads, eliminating the storage bottlenecks that stall pipelines, waste compute, and delay time to market.
The world’s leading manufacturing organizations are modernizing storage infrastructure with NeuralMesh.
Faster Storage Performance Translates to Faster Design Cycles, More Iterations, and Fewer Delays
Legacy NAS systems were not built to handle the concurrency, throughput, and metadata demands of modern manufacturing. In an age of massive datasets and faster workflows, manufacturing teams need infrastructure that removes bottlenecks and improves outcomes on the factory floor. Combined, NeuralMesh, NeuralMesh™ Axon™ and Augmented Memory Grid™ can deliver the speed and performance needed to support manufacturing workflows.
Reduce Failure-Driven Overhead Expenses
Maintain peak multi-tenant performance, achieve sub-millisecond latency, and process intel faster for actionable quality control and factory floor decision-making
Streamline End-to-End
AI Workflows
Host manufacturing workflows in a single, trusted infrastructure to dynamically support workflows from data ingestion, to training, to model deployment and inference
Evolve Beyond Legacy
HPC Infrastructure
Scale to exabytes without architectural limitations or performance degradation to transition smoothly from traditional HPC architectures to AI-ready data pipelines
Maximize Overall Infrastructure Utilization
Offer fast, frequent checkpointing to feed GPU & CPU compute resources continuously with a zero-copy, high-throughput data path
Build for Highly
Regulated Environments
Protect and expedite multi-day CFD and FEA simulation runs with high levels of I/O accuracy and reliable mid-run checkpointing at scale
Offer Unparalleled Performance Density
Improve metadata efficiency and optimize for lots of small files to reduce overall energy consumption and infrastructure footprint
NeuralMesh Delivers the Speed and Reliability to Keep Manufacturing Moving
Chip design, predictive maintenance, and factory floor analysis all require secure, low-latency, and high performance data storage. NeuralMesh helps to support the full manufacturing workflow across dozens of manufacturing specialties.
Defect Detection and Predictive Maintenance
Real-time, continuous analysis of sensor and telemetry data from GPU-based computer vision enables early detection of failure signals, minimizes unplanned downtime, and extends machine lifespan. NeuralMesh maintains the continuous small-file ingest these pipelines require without latency degradation.
Automotive Manufacturing
In automotive manufacturing workflows, legacy storage idles expensive GPU farms during vehicle simulation, creating a bottleneck that forces re-spins. NeuralMesh’s shared architecture absorbs complex simulation loads to accelerate design cycles.
Robotics
Robotics training involves many concurrent streams, including LIDAR, camera, telemetry, timestamps, and others, each requiring frequent model checkpointing. NeuralMesh removes siloed infrastructure to support the continuous data loop from edge devices to data center and back.
Aerospace and Defense
A&D simulation runs require massive parallelism and low-latency writes to prevent lost jobs or wasted compute cycles. NeuralMesh analyzes real-time data from IoT devices and sensors, enabling faster intelligence processing and more immediate actionable decisions.
Industrial
Industrial manufacturers face severe storage bottlenecks from complex simulations, digital twins, and IoT telemetry that starve expensive compute resources and stall production cycles. NeuralMesh eliminates these constraints through a distributed, parallel data architecture that delivers ultra-low latency, ensuring GPUs remain fully saturated to accelerate engineering iterations and time-to-market.
Semiconductor Fabrication
Semiconductor Fab workflows write terabytes per time step across hundreds of concurrent simulations, causing legacy storage to break down and require repeated design iterations. NeuralMesh delivers the throughput and checkpoint reliability that keep tapeouts on schedule and re-spin costs off the books.
Chip Design
Hundreds of concurrent EDA jobs share massive design databases where metadata performance determines whether tool farms run or stall. NeuralMesh handles the mixed-workload, high-throughput demands of advanced chip design to keep tapeouts on track.
NeuralMesh Offers a Proven Solution for Manufacturing Teams
“We needed a data storage solution that works out of the box for large-scale AI training and data management, handling the heavy lifting and the small details for us so we can stay focused and move fast.”
“WEKA’s storage scalability and ability to grow the infrastructure without losing performance, was a key factor in the decision to select the Weka file system.”
“Choosing WEKA in a public cloud environment was the optimal decision for maximizing performance, and it really made a difference in accelerating our multi-node AI training.”
“You need to have a higher and higher transferring speed… the source is of course the storage system that needs to be capable of actually delivering all this data at the right speed.”
“WEKA turns unused local NVMes into a high-performance shared storage system that is resilient and available… [leading to 100% data portability across diverse deployment types].”
After comparisons with legacy NFS-based NAS storage solutions, Innoviz selected WEKA because performance improvements with WEKA matched the company’s needs.
This emerging robotics startup ramped up AI model training with NeuralMesh Axon’s efficient data infrastructure to handle metadata-heavy, I/O-intensive workloads.
“For the same hardware, [WEKA] can deliver data faster, thus allowing you to feed more of these GPUs and fill their memory just in time for you to do the processing.”
Choose NeuralMesh and Accelerate Manufacturing Innovation
Every major design breakthrough and production cycle depends on data being captured, processed, analyzed, and stored efficiently. When infrastructure becomes a bottleneck, design iterations stall, and time-to-market is delayed. When infrastructure performs at scale, manufacturing innovation accelerates. Ready to see what’s possible with NeuralMesh?
Common Questions, Straight Answers
It removes storage bottlenecks that stall GPUs during CAE simulations. High-performance storage ensures concurrent data access, allowing engineering teams to run faster iterations and speed time-to-market.
Bottlenecks cause “GPU starvation,” where costly clusters wait for data. This spikes simulation runtimes, forces design re-spins, and delays robotics pipelines, drastically reducing overall infrastructure ROI.
A parallel, distributed file system is ideal. NeuralMesh AIDP™ uses the proprietary Augmented Memory Grid™ to deliver infrastructure optimized for analytics, ensuring seamless GPU optimization and parallel access.
Advanced platforms handle massive IoT telemetry by scaling capacity independently. Distributed systems like WEKA NeuralMesh scale seamlessly across edge, core, and cloud environments without disruptive upgrades.
It lets teams burst to hyperscale clouds while keeping IP secure on-premises. Appliances like WEKApod let teams deploy storage simply, streamlining compliance and secure data mobility across global sites.
Teams boost GPU utilization by using parallel architectures to feed multi-modal data to compute cores. WEKA ensures autonomous systems access data simultaneously, keeping GPUs saturated to reduce training time.
It dictates output limits. Building AI factories with distributed architectures achieves higher throughput per watt, enabling larger simulations without expanding footprints or missing sustainability targets.
Legacy storage failures disrupt operations. Modern distributed architectures use Intelligent Fast Rebuilds to maintain high availability, ensuring critical factory production loops stay online during component failures.