TensorWave

TensorWave is a cloud computing company based in Las Vegas, Nevada, specialising in AI workloads. It offers AMD Instinct MI300X accelerators for AI training, fine-tuning, and inference. The company was founded in December 2023 by Darrick Horton, Jeff Tatarchuk, and Piotr Tomasik. It operates as a private, for-profit organisation.

TensorWave provides cloud services designed to improve AI performance. It supports PyTorch and TensorFlow natively, requiring no modifications. Its infrastructure offers two options: bare-metal nodes and fully-managed Kubernetes clusters. The company aims to provide cost-effective AI computing while maintaining performance and security.

A key feature of TensorWave is its comparison with Nvidia's H100 GPUs. The MI300X accelerators offer 2.4 times more memory capacity, 1.6 times more memory bandwidth, 1.3 times more streaming processors, and 2.4 times more FP8 TFLOPS. The platform ensures faster performance and lower costs.

TensorWave’s products include:

• MI300X Cloud – A cloud service for AI workloads.
• TensorNODE – AI cloud infrastructure with a petabyte-scale GPU memory pool.
• FabreX – GigaIO’s memory fabric technology for scalable AI computing.

The company has raised approximately $46.2 million in funding, with investors including Nexus VP and Cadenza. It has 11-50 employees and 39 listed members on LinkedIn. TensorWave maintains strict data security standards, holding SOC2 Type II certification and HIPAA compliance.

Recent news includes a 1GW AI infrastructure deal with Tecfusions and coverage on platforms like NYSE Wired and The Register. The company is onboarding early access clients and offers a demo for testing its performance.

TensorWave positions itself as a competitor to Nvidia in AI computing, focusing on better price-performance, immediate availability, and enhanced security for AI applications.

TensorWave was founded in December 2023 in Las Vegas, Nevada, by Darrick Horton, Jeff Tatarchuk, and Piotr Tomasik. The company was created to address the growing demand for AI-focused cloud computing solutions. 

It focused on developing a cloud platform that could provide efficient, cost-effective AI training, fine-tuning, and inference. The founders saw an opportunity to offer an alternative to Nvidia's dominance in the AI computing market by integrating AMD’s Instinct MI300X accelerators into their infrastructure.

From the beginning, TensorWave designed its platform to support AI workloads with better memory capacity and processing power. The company introduced MI300X Cloud, a cloud-based solution built specifically for AI training. It also launched TensorNODE, an AI cloud infrastructure designed with a petabyte-scale GPU memory pool to support large-scale AI computations. To improve system efficiency, TensorWave integrated FabreX, GigaIO’s memory fabric technology, enabling scalable AI computing.

The company positioned itself as a first-to-market provider for MI300X-powered cloud computing. Its services offered immediate availability of AMD MI300X accelerators, allowing clients to deploy AI workloads quickly. TensorWave also provided options for both bare-metal nodes and fully managed Kubernetes clusters to meet different client requirements. The platform supported PyTorch and TensorFlow natively, ensuring seamless integration without code modifications.

As part of its growth, TensorWave secured funding of approximately $46.2 million from investors, including Nexus VP and Cadenza. The company also maintained industry security standards, obtaining SOC2 Type II certification and HIPAA compliance. It focused on providing a private and secure environment for AI applications.

By late 2024, TensorWave gained industry attention with key partnerships and projects. It signed a 1GW AI infrastructure deal with Tecfusions, expanding its presence in the AI cloud market. The company was featured in major publications, including NYSE Wired, The Register, and PR Newswire. 

It continued to position itself as a competitor to Nvidia, offering a lower total cost of ownership and improved AI computing performance. TensorWave remains focused on expanding its AI cloud services, onboarding early access clients, and offering demo opportunities for businesses interested in testing its platform.

TensorWave’s mission is to provide high-performance cloud computing solutions for AI workloads. The company focuses on offering efficient, scalable, and cost-effective AI training, fine-tuning, and inference. By using AMD Instinct MI300X accelerators, TensorWave aims to improve AI processing speed and reduce costs. It ensures seamless integration with AI frameworks like PyTorch and TensorFlow, allowing businesses to deploy AI applications without extra modifications. The company is committed to maintaining strong security and compliance standards, including SOC2 Type II and HIPAA certifications. TensorWave’s goal is to enable businesses to harness AI technology effectively while ensuring privacy, security, and accessibility.

TensorWave envisions a future where AI computing is accessible, scalable, and efficient for businesses of all sizes. The company aims to lead in AI cloud solutions by providing an alternative to existing GPU providers. It seeks to create a computing environment that enhances AI performance while reducing costs. By continuously developing its cloud infrastructure, TensorWave plans to support emerging AI applications across industries. The company’s vision includes expanding partnerships, improving AI processing capabilities, and maintaining strict security standards. TensorWave strives to be a reliable platform for AI innovation, ensuring businesses can train and deploy AI models with ease.

TensorWave has gained industry recognition for its contributions to AI cloud computing. It is one of the first-to-market providers of AMD Instinct MI300X accelerators, making AI computing more efficient and cost-effective. The company has been featured in NYSE Wired, The Register, and PR Newswire, highlighting its role in AI infrastructure development. TensorWave has also secured a 1GW AI infrastructure deal with Tecfusions, marking a significant achievement in AI cloud services. Additionally, it holds SOC2 Type II certification and HIPAA compliance, ensuring high security and data protection standards. TensorWave continues to be recognised for its innovation in AI computing.

TensorWave provides cloud computing solutions designed for AI workloads. The company focuses on training, fine-tuning, and inference by offering high-performance AI infrastructure powered by AMD Instinct MI300X accelerators. Its products and services aim to improve AI processing speed, scalability, and cost-effectiveness while ensuring data security and seamless integration with AI frameworks.

MI300X Cloud is TensorWave’s core cloud service, built specifically for AI applications. It allows businesses to run AI training and inference workloads with high efficiency. The platform is optimised for deep learning models and supports frameworks such as PyTorch and TensorFlow without requiring code modifications. MI300X Cloud offers better memory capacity and processing power compared to traditional AI cloud services. The system provides 2.4 times more memory capacity, 1.6 times more memory bandwidth, 1.3 times more streaming processors, and 2.4 times more FP8 TFLOPS compared to Nvidia’s H100 GPUs. This makes it a strong alternative for AI-driven businesses looking for high performance at a lower cost.

TensorNODE is a specialised AI cloud infrastructure designed to handle large-scale AI workloads. It features a petabyte-scale GPU memory pool, enabling efficient AI training and inference for complex models. TensorNODE is built for enterprises that require high-performance computing resources for deep learning, generative AI, and other machine learning applications. Businesses can choose between bare-metal nodes or fully-managed Kubernetes clusters, depending on their computing needs. The bare-metal option provides direct access to raw GPU power, while the managed service ensures an optimised and scalable AI environment without requiring extensive IT management.

FabreX is an advanced memory fabric technology developed by GigaIO and integrated into TensorNODE. It enhances AI computing by linking multiple GPUs efficiently, improving overall system performance. This technology helps businesses scale their AI workloads without facing memory or data transfer limitations. FabreX ensures that AI models run faster and can handle larger datasets more effectively, making it a key component of TensorWave’s AI infrastructure.

TensorWave’s cloud services provide seamless integration with existing AI workflows. Businesses can deploy their AI applications without making any changes to their code, as the platform supports popular AI frameworks out-of-the-box. This makes it easier for enterprises to transition to TensorWave’s cloud without additional development work.

Security is a key part of TensorWave’s services. The company is SOC2 Type II certified and HIPAA compliant, ensuring that customer data is protected. The platform offers private, secure, and segregated computing environments, making it suitable for businesses handling sensitive AI workloads.

TensorWave also focuses on cost efficiency. The platform offers a lower total cost of ownership (TCO) while maintaining high performance. By using AMD MI300X accelerators, TensorWave provides a more affordable alternative to Nvidia-based cloud solutions. The company’s pricing model ensures that businesses can scale their AI workloads without exceeding their budgets.

TensorWave is actively onboarding early access clients to test its platform. It offers demos for businesses interested in evaluating its AI cloud services. The company’s goal is to provide a reliable, secure, and scalable AI infrastructure that helps businesses train, fine-tune, and deploy AI models efficiently.