The Integrated Lifecycle

At the heart of eFabric™ is a commitment to consolidation.
The platform is not just a training tool — it is an End-to-End Lifecycle Manager.

Understanding the End-to-End Workflow

The eFabric™ journey is consolidated into a single intuitive interface that guides you through six critical steps:

Create Project: Initialize your workspace with optimized defaults.
Import Data: Seamlessly upload and label your datasets.
Preprocess: Configure advanced DSP (Digital Signal Processing) pipelines.
Build Model: Use AutoML templates or design custom architectures.
Train & Validate: Monitor live metrics and logs to ensure model accuracy.
Deploy: Export your optimized model and flash directly to the chip.

Eliminating External Toolchains and SDKs

One of the primary advantages of this unified approach is the elimination of external tools. You no longer need to jump between third-party labeling software, cloud training services and hardware-specific IDEs. Everything happens within the eFabric™ Dashboard Link, significantly reducing complexity and security risks.

Version Control in ML Projects

Maintaining different versions of an AI model is notoriously difficult. eFabric™ integrates versioning directly into the lifecycle, allowing you to track changes in your datasets and training parameters. This ensures that every .synpkg (silicon package) generated is traceable to the exact data and settings used to create it.

“Ready to see the factory in action? Explore our Tutorials Link to start your first project.”