Managed AI infrastructure platform - AI tools

Mirantis k0rdent AI provides unified management for AI application and platform workloads across hybrid, multi-cloud, and edge environments, ensuring efficiency, compliance, and scalability for enterprises.

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Cirrascale AI Innovation Cloud offers comprehensive cloud infrastructure for AI workloads, providing access to multiple leading AI accelerators including NVIDIA, AMD, and Cerebras systems with no data transfer fees and high-performance computing capabilities.

• Paid
• From 259$

Ai Pool™ provides a supercomputing infrastructure platform, Excalibur™, for businesses, investors, and entrepreneurs to build, train, deploy, and host their AI applications and models cost-effectively and at scale.

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UbiOps provides a unified interface to run AI workloads across various infrastructures, including local, hybrid, and multi-cloud environments. It simplifies AI production, reduces costs, and prevents vendor lock-in.

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Deep Infra is a serverless ML platform offering access to top AI models through a simple API, with pay-per-use pricing and automatic scaling capabilities.

• Usage Based

DigitalOcean delivers scalable cloud computing solutions and AI tools, making it easy for developers and businesses to build, deploy, and manage applications with predictable pricing.

• Usage Based
• From 4$

Spice.ai is an enterprise-grade platform that provides composable, ready-to-use data and AI infrastructure, offering SQL query capabilities, vector search, and model serving in a single AI backend-as-a-service.

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FlexAI provides universal AI compute, empowering developers to build and deploy AI solutions seamlessly across various hardware architectures. They optimize workload and energy efficiency for AI infrastructure.

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Denvr Cloud is a comprehensive cloud platform offering on-demand and dedicated accelerated computing solutions for AI inference and training, featuring state-of-the-art NVIDIA GPUs and Intel AI accelerators.

• Usage Based

/ML offers a full-stack AI infrastructure for serving large language models, training multi-modal models on GPUs, and hosting AI applications such as Streamlit, Gradio, and Dash, while providing cost observability.

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