Build specialized AI.Without starting over.
Alpha framework
Apache 2.0 / PyPI
NexuML helps engineers compose reusable machine-learning components, run reproducible experiments and develop specialized models without rebuilding the supporting workflow.
In development / separate from the installable alpha framework
NexuML Studio. A development preview.
Connected pipeline stages — faithful excerpt of the same development UI. Scroll sideways if needed; open full size for the complete view. Inspect focused capture (new tab)
Developer workflow
Change the experiment. Keep the reusable parts.
- 01
Compose
Resolve the scenario into a validated configuration; build its connected data and model stages before training.
- 02
Train & evaluate
Train with the scenario’s validation and test lifecycle and inspect logged metrics and configured evaluation results.
- 03
Export & reuse
Export models for use after centralized training, or reuse compatible models for further learning through NexuFL.
Open source / extensible
Open source. Your own starting point.
NexuML works without NexuFL. Use the framework for standalone development. External component libraries can extend the parts your task needs.
The public framework is Apache 2.0 licensed, marked alpha and available on PyPI. Alpha is not a production-readiness guarantee.
Python 3.12+ / Framework + reusable base library
pip install "nexuml[library]"- Source code / Apache 2.0
- Inspect the framework and its current implementation.
- Documentation and API reference
- Start from maintained scenario, training, evaluation and export guides.
- Hands-on tutorial projects
- Concrete examples with their own setup and data requirements.
- PyPI package / alpha
- Review the current package, Python requirements and release metadata.