Radicalbit AI Monitoring provides a solution for monitoring machine learning models in production.
The Best Ludwig Alternatives in 2026
Looking for something like Ludwig? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 22 are open source.
Ludwig provides a low code framework for building custom LLMs, neural networks, and other AI models.
Top picks at a glance
Quick comparison
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Radicalbit | — | Yes | — |
| 2 | BudgetML | — | Yes | — |
| 3 | ChefBoost | — | Yes | — |
| 4 | Datumbox | — | Yes | — |
| 5 | PyToune | — | Yes | — |
| 6 | Maze | — | Not stated | — |
| 7 | Aeromancy | — | Yes | — |
| 8 | PyTorch Lightning | — | Yes | — |
| 9 | Deepchecks | — | Yes | — |
| 10 | Feathr | — | Yes | — |
All Ludwig alternatives
Deploy a ML inference service on a budget in less than 10 lines of code.
The ChefBoost Python framework supports decision trees such as ID3, C4.5, CART, CHAID, regression trees, and ensemble methods.
The Datumbox framework is written in Java for developing machine learning and statistical applications.
PyToune provides a simplified framework and utilities for working with PyTorch.
Maze
github.com/enlite-ai/mazeMaze provides an applied reinforcement learning framework for developing projects in Python.
Use Aeromancy to build reproducible machine learning workflows and projects.
PyTorch Lightning supports pretraining and fine tuning AI models across GPU setups.
Deepchecks tests and validates machine learning models and data, covering workflows from research through production.
Feathr provides enterprises with a platform for data engineering and AI workflows.
Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
TPOT uses genetic programming to optimize machine learning pipelines in Python.
Ray provides an AI compute engine with a distributed runtime and libraries for machine learning workloads.
Evidently evaluates, tests, and monitors machine learning systems and data pipelines.
MLRun provides an open-source MLOps platform for managing machine learning applications, pipelines, and CI/CD delivery.
FLAML provides a fast Python library for automated machine learning and tuning.
The Feast repository describes an open source feature store for AI and machine learning projects.
Kedro
github.com/quantumblacklabs/kedroKedro helps create reproducible, maintainable, and modular data science and data engineering pipelines.
FlexML offers an easy to use and flexible automated machine learning library for Python.
Polyaxon describes its repository as infrastructure for AI orchestration and control.
ZenML provides a platform for machine learning pipelines and AI agents.
The goro project provides a high level machine learning library written for Go.
This Docker-based starter kit provides a runtime for machine learning work in Jupyter notebooks.
Featureform turns existing data infrastructure into a virtual feature store.
Alternatives to similar tools
What is the best alternative to Ludwig?
Are there open-source alternatives to Ludwig?
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative
























