Optimize AI models for edge devices - AI tools

EDGENeural.ai is an end-to-end platform that enables AI developers to train, optimize, and deploy deep learning models on edge devices, reducing development time from months to hours.

• Freemium

CLIKA provides an AI model compression engine to optimize models for speed, size, and hardware deployment, reducing memory footprint and enhancing performance.

• Freemium

Nexa AI is an on-device Generative AI development platform enabling businesses and developers to build and deploy high-performance, optimized AI applications locally across any hardware.

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Latent AI's Efficient Inference Platform (LEIP) is an enterprise AI solution that enables efficient development and deployment of machine learning models at the edge, reducing cloud dependency and operational costs.

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Aptos is a no-code MLOps toolchain designed to optimize and deploy machine learning models for low-power edge devices. It simplifies edge AI development and enhances model efficiency.

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ZETIC.ai is a cutting-edge platform that enables companies to transform their AI operations to on-device processing, eliminating GPU cloud dependencies while delivering superior performance and cost savings.

• Free Trial

Qualcomm AI Hub is a comprehensive platform for deploying and optimizing AI models on Qualcomm devices, offering seamless integration with various runtimes and support for multiple industries including mobile, compute, automotive, and IoT.

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Edge Impulse is the leading edge AI development platform, accelerating the delivery of next-generation products and solutions by bringing intelligence to any edge device.

• Freemium
• From 400$

Neuton TinyML is a no-code automated platform that builds extremely compact neural networks for microcontrollers and sensors, enabling AI capabilities on edge devices with models as small as 5KB.

• Freemium