Hailo AI Software Suite
Product InquiryHailo devices are accompanied by a comprehensive AI software suite that enables the compilation of deep learning models and the implementation of AI applications in production environments. The model build environment seamlessly integrates with common ML frameworks to allow smooth and easy integration in existing development ecosystems. The runtime environment enables integration and deployment in host processors, such as x86 and ARM based products, when utilizing Hailo-8™, and in Hailo-15™ vision processor.
Hailo Software Suite includes the following key components
Model Build Environment
Model Zoo, a variety of common and state-of-the-art pre-trained models and tasks in TensorFlow and ONNX.
Hailo Dataflow Compiler, for offline compilation and optimization of user’s models for Hailo devices
Runtime Environment
Hailo TAPPAS, set of full application examples, implementing pipeline elements and pre-trained AI tasks
HailoRT production-grade and light runtime software package, running on the host processor for real-time inferencing the deep learning models compiled by the Dataflow Compiler
Hailo Software Suite includes the following key components
Model Build Environment
Model Zoo, a variety of common and state-of-the-art pre-trained models and tasks in TensorFlow and ONNX.
Hailo Dataflow Compiler, for offline compilation and optimization of user’s models for Hailo devices
Runtime Environment
Hailo TAPPAS, set of full application examples, implementing pipeline elements and pre-trained AI tasks
HailoRT production-grade and light runtime software package running on Hailo-15™ for real-time inferencing the deep learning models compiled by the Dataflow Compiler.
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Other Products
Breathe life into your edge products
with the Hailo-8™ AI processor
EU Research and Innovation Program
This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 849921
This project has received funding from the European Union’s Horizon 2020.