LEIP Optimize: Edge AI Optimization Simplified

Automate rapid hardware and software optimization of ML models without requiring hardware expertise.

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Rapid prototyping to any device

See all the model metrics.

Analyze size, accuracy, and power trade-offs interactively to meet your exact criteria.

Switch hardware platforms without restarting the design process.

Software Developers

Design, optimize, and deploy models to your app regardless of skill—without writing a line of Python.

Use a powerful visualizer to choose the best model-hardware combination for your project from over 50K benchmarked configurations.

Analyze size, accuracy, and power trade-offs interactively to meet your exact criteria.

Reuse a trusted, modular pipeline to apply different models and/or hardware to the same dataset and deploy without changing dependencies, applications, or hardware.

Product Managers

Transform your products by enabling actionable insights powered by edge AI.

Reduce your time to market with a scalable, repeatable ML pipeline.

Add predictable ML to your apps with benchmarked and ready-to-execute configurations that combine model and device optimization on your data.

Empower everyone, regardless of AI expertise, to design, train, and deploy models to edge devices.

Intuitive for Beginners, Powerful for Experts

Bring your model to a framework that simplifies the processes of compiling, optimizing, and quantizing machine learning models, making these complex tasks accessible to a wider range of users.

Introducing Forge

Target hardware without in-depth hardware knowledge or expertise.

Improve inference speed by optimizing the model and leveraging all acceleration on your target hardware.

Speed up model predictions via quantization and shrink to run in lower-bit precision (INT8) while preserving accuracy.

Convert a machine learning model to a single portable file.

Build your own tools on top of Forge.

Agnostic model ingestion

Import your own model into a framework designed to accept models from a variety of sources.

Supports computer vision models and most models with dynamic tensors, such as transformers.

Ingest any model including models from popular frameworks like Tensorflow, PyTorch, and Onnx. Including the majority of computer vision models on Hugging Face.

Easy integration into your current ML environment to give you tooling flexibility and familiarity.

Accelerate prototyping

Test and evaluate optimization for various model-hardware combinations.

Optimize and encrypt multiple models for one or more hardware targets, enhancing workflow without requiring hardware expertise.

Script optimization and compilation jobs for reusability and automation.

Expert precision control

Manipulate your models with our direct graph manipulation tool to debug and modify incompatible models for specific hardware.

Explore the design space for further optimization.

Add in your own watermark to protect your models.