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The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
☁️ Build multimodal AI applications with cloud-native stack
Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.
Always know what to expect from your data.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.
Build, Manage and Deploy AI/ML Systems
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
The Open Source Feature Store for AI/ML
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
Superduper: End-to-end framework for building custom AI applications and agents.
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
Train and Deploy an ML REST API to predict crypto prices, in 10 steps
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
Kraken CI is a continuous integration and testing system.
Lightweight version of TensorFlow with the same functionality: It never works and only outputs errors.
Open, audit-grade agentic data quality framework with portable industry packs