# WEKA

> WEKA is an AI storage company building the NeuralMesh ecosystem — a high-performance, software-defined data platform purpose-built for accelerated compute and agentic AI infrastructure. NeuralMesh combines GPU-native storage, augmented memory, and turnkey appliances to help organizations eliminate data bottlenecks, maximize GPU utilization, and scale AI workloads from training to inference.

## Products

- [NeuralMesh](https://www.weka.io/product/neuralmesh/): High-performance, container-native storage system purpose-built for AI training, inference, and data-intensive workloads at scale
- [NeuralMesh Axon](https://www.weka.io/product/neuralmesh-axon/): GPU-native AI storage delivering ultra-low latency and high throughput directly to accelerated compute
- [WEKApod](https://www.weka.io/product/wekapod/): Turnkey data platform appliance designed for NVIDIA DGX SuperPOD with pre-configured storage and software for rapid deployment
- [Augmented Memory Grid](https://www.weka.io/product/augmented-memory-grid/): Extends GPU memory up to 1000x, unlocking larger models and longer context windows without additional hardware
- [NeuralMesh AIDP](https://www.weka.io/product/neuralmesh-aidp/): Integrated AI data platform combining storage, memory, and orchestration for full AI factory workflows
- [NeuralMesh Capabilities](https://www.weka.io/product/capabilities/): Full technical capability overview including POSIX, NFS, S3, SMB, GPUDirect Storage, snapshots, tiering, and encryption

## Deployment Options

- [AI Data Center](https://www.weka.io/product/ai-data-center/): On-premises NeuralMesh deployment for private AI data centers and GPU clusters
- [Public Cloud](https://www.weka.io/product/public-cloud/): NeuralMesh on AWS, Azure, and GCP for cloud-native AI workloads
- [Hybrid Cloud](https://www.weka.io/product/hybrid-cloud-storage/): Unified storage spanning on-premises and cloud environments with a single namespace
- [AI Cloud Providers](https://www.weka.io/product/ai-cloud-providers/): Purpose-built storage infrastructure for GPU cloud and neocloud providers

## Solutions by Use Case

- [AI Factory](https://www.weka.io/solutions/ai-factory/): End-to-end AI factory infrastructure from data ingestion and training to inference and production delivery
- [AI Inference Acceleration](https://www.weka.io/solutions/ai-inference-acceleration/): Low-latency storage optimized for real-time AI inference and agentic workloads
- [Generative AI](https://www.weka.io/solutions/weka-for-generative-ai/): Storage infrastructure for training and serving large language models and foundation models
- [Reduce AI Token Costs](https://www.weka.io/solutions/reduce-ai-token-costs/): Architectural approach to increasing token efficiency and cutting AI infrastructure costs
- [GPU Acceleration](https://www.weka.io/solutions/gpu-acceleration/): Maximize GPU utilization by eliminating storage bottlenecks in accelerated compute environments
- [High-Performance Computing](https://www.weka.io/solutions/hpc-data-management/): All-flash parallel file system performance for HPC workloads without complexity tradeoffs
- [High-Performance Data Analytics](https://www.weka.io/solutions/high-performance-data-analytics/): Fast data pipelines for analytics at data warehouse performance on all-flash infrastructure
- [AI & Machine Learning](https://www.weka.io/solutions/ai-machine-learning/): Unified storage for the full ML lifecycle from data prep to model training to deployment
- [Containerized Workloads](https://www.weka.io/solutions/containerized-applications/): High-performance persistent storage for Kubernetes and containerized AI workloads
- [Cloud Service Providers](https://www.weka.io/solutions/specialized-cloud-services/): Scalable AI storage infrastructure for GPU clouds and cloud service providers

## Solutions by Industry

- [Government Agencies](https://www.weka.io/solutions/government-agencies/): Secure, high-performance AI storage for defense, intelligence, and civilian government workloads
- [Financial Services](https://www.weka.io/solutions/financial-services/): Low-latency AI data infrastructure for trading, risk modeling, and financial analytics
- [Healthcare & Life Sciences](https://www.weka.io/solutions/healthcare-life-sciences/): High-performance storage for genomics, medical imaging, drug discovery, and clinical AI
- [Media & Entertainment](https://www.weka.io/solutions/media-and-entertainment/): All-flash performance for rendering, VFX, post-production, and content pipelines

## Partners & Reference Architectures

- [WEKA x NVIDIA](https://www.weka.io/partners/nvidia/): Deep integration with NVIDIA DGX, HGX, GPUDirect Storage, and Magnum IO for GPU-accelerated AI
- [WEKA x DELL](https://www.weka.io/partners/dell/): Validated joint solutions combining DELL infrastructure with NeuralMesh software
- [NVIDIA DGX SuperPOD](https://www.weka.io/resources/reference-architecture/nvidia-dgx-superpod-with-wekapod-data-platform-appliance/): Reference architecture for WEKApod with NVIDIA DGX SuperPOD
- [NVIDIA DGX BasePOD](https://www.weka.io/resources/reference-architecture/weka-and-nvidia-dgx-basepod/): Reference architecture for NeuralMesh with NVIDIA DGX BasePOD
- [Amazon SageMaker HyperPod](https://www.weka.io/blog/cloud-storage/accelerate-distributed-model-training-with-weka-support-for-amazon-sagemaker-hyperpod/): Integration guide for distributed model training on AWS SageMaker HyperPod
- [WEKA AI RAG Reference Platform](https://www.weka.io/resources/reference-architecture/warrp-weka-ai-rag-reference-platform/): Reference architecture for building RAG pipelines on NeuralMesh
- [System Partners](https://www.weka.io/partners/system-partners/): Hardware and system integration partners
- [Cloud Partners](https://www.weka.io/partners/cloud-partners/): Cloud provider partnerships and validated configurations
- [Software Partners](https://www.weka.io/partners/software-partners/): ISV and software ecosystem integrations
- [Channel Partners](https://www.weka.io/partners/channel-partners/): Global reseller and channel partner network

## Technical Resources & Documentation

- [Product Documentation](https://docs.weka.io/): Full NeuralMesh documentation including getting started, filesystems, protocols, Kubernetes, security, and performance
- [NeuralMesh Architecture Whitepaper](https://www.weka.io/resources/white-paper/wekaio-architectural-whitepaper/): Deep-dive technical whitepaper on NeuralMesh architecture and design principles
- [WEKA AI RAG Reference Platform Whitepaper](https://www.weka.io/resources/white-paper/weka-ai-rag-reference-platform/): Technical guide to building RAG pipelines with NeuralMesh
- [Support Portal](https://support.weka.io/s): Customer support, knowledge base, and case management
- [Demos](https://www.weka.io/resources/demo/): Product demos and hands-on walkthroughs
- [Videos](https://www.weka.io/resources/video/): Technical videos, explainers, and customer stories
- [Glossary](https://www.weka.io/learn/glossary/): AI and storage terminology reference
- [Guides](https://www.weka.io/learn/guide/): Practical guides for AI infrastructure and storage

## Resources & Insights

- [Blog](https://www.weka.io/weka-blog-ai-storage-and-infrastructure-insights/): Articles on AI storage, GPU infrastructure, and industry trends
- [Asset Library](https://www.weka.io/resources/): Full library of white papers, solution briefs, data sheets, analyst reports, and infographics
- [Customers](https://www.weka.io/customers/): Case studies from CoreWeave, Hugging Face, Cohere, Stability AI, Nebius, Eleven Labs, Contextual AI, and more
- [Newsroom](https://www.weka.io/company/weka-newsroom/): Press releases, announcements, and media coverage
- [Events](https://www.weka.io/company/events/): Upcoming conferences, webinars, and WEKA-hosted events

## Company

- [Our Story](https://www.weka.io/company/our-story/): WEKA's founding story, mission, leadership team, and company background
- [Careers](https://www.weka.io/company/careers/): Open roles and information about working at WEKA
- [Sustainability](https://www.weka.io/company/sustainable-ai/): WEKA's approach to sustainable AI infrastructure
- [Contact Us](https://www.weka.io/company/contact-us/): Get in touch with WEKA sales, support, or partnerships