Top 50 Ai Compute Platform - Seed

The startup operates a cloud-based computing platform that provides AI-driven solutions for researchers and enterprises, focusing on large language model development, programmatic data labeling, and machine learning testing. It offers high-performance computing resources, including access to powerful GPUs and virtual machines, while promoting e-waste reduction through environmentally friendly practices.

This startup offers a comprehensive AI platform designed to meet diverse organizational needs. The platform likely provides various AI-powered tools and solutions, potentially covering areas like automation, analytics, and decision-making.

SambaNova Systems develops an enterprise-grade AI platform that integrates specialized hardware and software to efficiently deploy generative AI applications. This technology addresses the need for scalable, high-performance computing solutions that unlock valuable insights from complex data sets, enabling organizations to enhance operational efficiency and discover new revenue streams.

Compute Labs utilizes its Compute Tokenization Protocol to tokenize enterprise-grade GPUs, enabling trading, staking, and derivatives for compute assets. This approach allows investors to gain direct exposure to GPU-based yields and derivatives, facilitating participation in the growing AI compute market.

Provides a compute engine optimized for running multi-step AI workloads by analyzing and tuning workflows as directed acyclic graphs. Enables developers to build compound AI systems using modular components like models, vector databases, and code interpreters, improving performance through automatic workload optimization and maximum parallelism.

The startup provides AI supercomputers that configure and host GPU servers optimized for deep learning and high-performance computing (HPC) applications. This offering enables organizations to scale their computational resources efficiently while minimizing the infrastructure costs associated with AI workloads.

Thyris provides a cloud-based AI runtime that utilizes Kubernetes and CPU/RAM resources, eliminating the need for GPUs in AI applications. This technology enables organizations to deploy AI solutions more efficiently and cost-effectively, broadening access to advanced AI capabilities without the high infrastructure costs.

Berkeley Compute is a decentralized GPU platform that leverages blockchain technology to create a distributed network for artificial intelligence processing. This platform enables users to monetize their idle GPU resources, addressing the high costs and accessibility issues associated with traditional cloud computing services.

Kluisz.ai provides an AI-powered cloud platform for deploying and managing enterprise workloads across on-premises, edge, and hybrid environments. Its API-first architecture and zero-trust security principles enable seamless application composability and unified management for distributed computing resources.

XFA AI provides cloud-based GPU rentals through a user-friendly interface, enabling businesses to access high-performance computing resources without the need for significant upfront investment. This service reduces operational costs associated with GPU usage, making advanced computing more accessible for data-intensive applications.

Provides a cloud-based platform for training, fine-tuning, and deploying generative AI models, optimized with proprietary hardware-software integration to eliminate virtualization overhead. Radium’s architecture enables up to 50% faster training and 135% faster inference compared to traditional hyperscalers, supporting scalable, secure, and cost-efficient AI development for enterprises.

Starcloud builds hyperscale data centers in orbit to overcome the limitations of terrestrial infrastructure for AI training. These orbital facilities offer continuous solar energy and radiative cooling, enabling the deployment of massive computational resources unhindered by Earth-based constraints.

Cake provides a modular platform that integrates open-source AI components, compute management, and security features to streamline the development and deployment of AI projects. By offering pre-built integrations and auto-scaling capabilities, Cake reduces the time and resources required for businesses to implement production-ready AI solutions.

Thunder Compute develops software that virtualizes GPUs across a network, allowing users to connect any GPU to their cloud instance in real time without complex configuration. This technology reduces costs by enabling users to pay only for active GPU usage, eliminating expenses associated with idle resources.

The startup offers an artificial intelligence infrastructure platform that enhances the transparency of deep learning models by making their decision-making processes explainable. This platform provides insights into AI operations and optimizes cost management, eliminating the need for custom integration or extensive log analysis.

Provides a decentralized compute protocol that enables users to train and fine-tune AI models using a scalable SDK and access to exclusive GPU resources. Reduces machine learning training costs by up to 80% while ensuring data privacy, transparent model tracing, and instant autoscaling to eliminate idle compute time.

MAKO provides automated GPU kernel selection and tuning technology that enables the deployment of AI models with up to 70% lower computing costs across any hardware infrastructure. This solution eliminates the need for manual optimization and vendor lock-in, allowing businesses to efficiently scale their AI operations in any cloud or on-premises environment.

This company offers a unified control plane for managing diverse cloud infrastructure, simplifying cloud and container deployment across multiple providers. Their API software enables businesses to optimize compute costs and enhance operational flexibility.

Stelia provides a data mobility platform that facilitates seamless data transfer and accessibility across diverse AI infrastructures. This technology eliminates data silos and enhances data management, enabling organizations to optimize AI workflows and improve decision-making efficiency.

Crusoe provides clean computing infrastructure powered by stranded energy sources, specifically designed for AI workloads, including model training and scalable inference. This approach reduces operational costs and minimizes the environmental impact of the growing demand for computational resources in the digital economy.

The startup offers an artificial intelligence orchestration platform that simplifies model management, intelligent caching, and cost tracking for businesses. This platform enhances operational efficiency by optimizing performance and reducing costs, enabling seamless scalability.

Concertio provides AI-powered performance optimization tools that utilize autonomous software agents for real-time dynamic and static optimization of hardware and software systems. This technology enhances compute system performance by continuously monitoring and adjusting system settings to meet the demands of various applications, particularly in cloud data centers and IoT environments.

The startup operates a high-performance computing data center that provides local companies with essential HPC resources to meet increasing demand. Its platform features an AI marketplace for software developers, integrating a token economy to facilitate transactions and enable profit-sharing for AI application uploads.

The startup has developed a protocol tailored for the computational demands of global deep learning models in machine learning. This technology enhances processing efficiency and scalability, addressing the challenges of resource-intensive AI applications.

Apolo provides a white-label AI platform that integrates with existing data center infrastructure, enabling colocation and hybrid cloud providers to offer GPU-as-a-Service without the need for costly data migrations. This solution enhances operational efficiency by supporting AI development tools and seamlessly connecting with back-office applications like billing and ERP systems.

Lilypad offers a platform for AI model deployment, distribution, and monetization, connecting model creators with compute providers. Their platform combines a model marketplace, MLOps tools, and a distributed compute network to simplify scaling AI inference across various applications. This allows AI model creators to generate revenue and compute providers to monetize their resources.

The startup develops machine learning tools that provide a zero-configuration Python API for running open-source simulations and optimization tools in scientific research. This technology eliminates technical barriers in computational tools, enabling scientists and engineers to efficiently conduct complex analyses both on-premise and in the cloud.

Heurist AI provides serverless access to a decentralized network of open-source AI models, utilizing an Elastic Chain built with a ZK Stack for efficient smart contract execution. This platform enables users to leverage AI inference and training without the operational burdens of managing GPU servers, while also allowing community members to contribute compute power and earn tokens.

aZen DePin is a decentralized infrastructure that leverages blockchain to create a shared economy of computing power. It connects and manages global computing resources to form a stable, distributed network, supporting diverse applications.

This startup offers a privacy-preserving inference platform that allows AI models to run on encrypted data, ensuring user queries remain confidential. By utilizing fully homomorphic encryption, the platform enables AI providers to deploy models without accessing sensitive user data, protecting privacy from AI providers, cloud infrastructure, and intermediaries.

Inspire Semiconductor provides the Thunderbird accelerated computing platform, a "supercomputer-cluster-on-a-chip" solution for HPC and AI workloads. Its RISC-V architecture and all-CPU programming model offer energy efficiency and simplified development, reducing datacenter TCO and carbon footprint.

Deeplite provides AI optimization software that enhances the performance of deep neural networks by reducing their size and energy consumption. This technology enables faster inference times, making AI applications more efficient and cost-effective for various industries.

Provides a decentralized platform that aggregates idle GPU resources from data centers and independent providers worldwide, creating a scalable and cost-effective infrastructure for on-demand high-performance computing. This system addresses the shortage of AI-grade GPUs by enabling seamless access to thousands of GPUs, including H100s and A6000s, for applications like AI training, rendering, and scientific computation.

Cerebrum Technologies develops AI-driven solutions utilizing machine learning algorithms for natural language processing and computer vision to enhance operational efficiency and customer experiences across various sectors. Their technology unlocks new growth opportunities for businesses in an increasingly digital landscape by optimizing processes and improving decision-making capabilities.

Nuvia designs high-performance processors optimized for compute-intensive applications through advanced silicon architecture, significantly enhancing processing speed and energy efficiency. The company provides a solution for the increasing demand for computational power in data centers and high-performance computing environments.

Oumi offers an open-source platform for the end-to-end development and deployment of AI models, supporting pre-training, fine-tuning, and evaluation of text and multimodal architectures. It enables flexible deployment across diverse environments and helps users avoid vendor lock-in while accelerating AI research and development.

The startup develops an artificial intelligence-based cybersecurity platform that enhances the security of cloud infrastructure by providing personalized remediation for Infrastructure as Code (IaC) policy deviations. This technology ensures that security measures are integrated into cloud architecture without compromising functionality, design, or performance.

Lemony.ai by Uptime Industries is a ready-to-use B2B edge AI platform that enables businesses to deploy AI applications at the edge, minimizing latency and bandwidth usage. This platform addresses the challenge of integrating AI into existing infrastructure, allowing companies to enhance operational efficiency and decision-making in real-time.

The startup offers a cloud-based rendering platform that provides fast and scalable 3D rendering by efficiently matching computing workloads with available cloud resources. This technology enables architects, animators, and designers to lower costs and enhance productivity while meeting tight project deadlines across various 3D software and engines.

The startup offers an artificial intelligence-powered risk resolution platform that simplifies cloud risk remediation through automated code-based mitigation and remediation of vulnerabilities and misconfigurations. This enables security and development operations teams to efficiently address open security issues, significantly reducing the time required for remediation.

BentoML provides a Unified Inference Platform that enables developers to build and deploy scalable AI systems using any model on their preferred cloud infrastructure. The platform addresses the challenges of slow iteration and high costs in AI deployment by offering features like auto-scaling, low-latency serving, and seamless integration with existing cloud resources.

Arcus provides a Machine Intelligence Platform that enables businesses to create complex, data-driven AI workflows capable of processing multi-modal, unstructured data and integrating with external APIs. This technology allows organizations to automate critical business processes, such as generating reports and performing numerical computations, thereby enhancing operational efficiency and decision-making.

The startup develops a neuromorphic chip that mimics human brain information-processing mechanisms to enhance artificial intelligence hardware. This technology addresses computing bottlenecks by enabling more efficient training of neural networks for AI applications.

Amplication provides a platform for building AI-powered applications through its specialized AI plugins. This enables developers to streamline application development and enhance functionality without extensive coding, addressing the complexity and time constraints often faced in software creation.

The startup develops a cloud-based computational chemistry platform that utilizes advanced chemical simulations to streamline the design and testing of chemical and pharmaceutical products. By providing a user-friendly interface and robust security features, the platform accelerates product development while ensuring data integrity.

Oumi provides an open-source AI platform for building, evaluating, and deploying AI models at scale. It enables researchers, developers, and enterprises to develop and own their AI solutions without proprietary vendor lock-in.

The startup develops AI processors that mimic human brain architecture to enhance energy efficiency and reduce complexity in AI systems. By addressing the limitations of current chip technology, their solutions enable clients to achieve high performance with minimal power consumption.

This startup is developing a personal computing platform that utilizes AI and large language models to enable natural language interaction and automation with user data and applications. By transforming rigid software environments into flexible, personalized computing experiences, it empowers users to efficiently organize tasks and achieve individualized goals.

Provides a multi-cloud AI compute platform that enables real-time GPU resource management, workload migration, and cost optimization across major cloud vendors. By reducing cluster provisioning times to minutes and supporting multi-node training with fixed budgets, it streamlines AI development and inference while maximizing GPU utilization and reducing operational overhead.

Hoonify provides a high-performance computing platform powered by its TurbOS operating system, which transforms standard computing systems into parallel computing resources capable of executing complex modeling, simulation, and machine learning tasks at supercomputer speeds. This solution enables businesses to enhance productivity and efficiency while maintaining data security and optimizing resource utilization in demanding computational environments.