Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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.
Machine Learning Engineering Open Book
The absolute trainer to light up AI agents.
An orchestration platform for the development, production, and observation of data assets.
Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
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
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
The Open Source Feature Store for AI/ML
ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
🐢 Open-Source Evaluation & Testing library for LLM Agents
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
Curated list of the best truly open-source AI projects, models, tools, and infrastructure. Daily updated.
⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers / verl / LLaMA Factory / ms-swift / Ultralytics / MMEngine / Keras etc.
Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.
Open-source inference server and production cluster for all the models your agent needs.
Community maintained hardware plugin for vLLM on Huawei Ascend
The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure
Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.
cubestudio开源云原生一站式机器学习/深度学习/大模型AI平台/MaaS/mlops/人工智能平台/训推平台,算法全链路流程,多租户,算力租赁平台,token中转,拖拉拽任务流pipeline编排,多机多卡分布式训练,超参搜索,推理服务,VGPU虚拟化,云边端协同,边缘计算,自动化标注平台,deepseek等大模型sft微调/奖励模型/强化学习训练,vllm/ollama/mindie大模型多机推理,私有知识库llmops智能体,AI模型市场,支持国产异构算力调度,昇腾/寒武纪/海光/摩尔/沐曦等,支持ib/roce/RDMA,信创支持
Open Source AI Accelerator Research Platform Standard / 开源推理研究平台
Automated Machine Learning on Kubernetes
MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.
Production-shaped MLOps Python package and reference implementation of the MLOps Coding Course: MLflow, scikit-learn, Pydantic, Pandera, uv, and mise.
A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
LightlyStudio - The Unified Data Platform for Multimodal ML
Exercises and supplementary material for the machine learning operations course at DTU.
NucliaDB, The AI Search database for RAG
Collective Knowledge (CK), Collective Mind (CM/CMX) and MLPerf automations: community-driven projects to learn how to run AI, ML, and other emerging workloads more efficiently and cost-effectively across diverse models, datasets, software, and hardware using MLPerf methodology and benchmarks.
skops is a Python library helping you share your scikit-learn based models and put them in production
Examples for Cerebrium Serverless GPUs
A curated collection of resources, tools, practices, case studies, and opportunities for Forward Deployed Engineers.
Evaluator-neutral AI evaluation evidence, baseline regression gates, and JSON, JUnit, and SARIF reports for CI.
Production-style end-to-end e-commerce recommendation platform with data engineering, MLOps, serving, governance, and observability on Kubernetes.
Distill a repeated Jev classification task into a local model, on the fly — same answers, your hardware.
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Static reproducibility checks, experiment replay, and verification for ML pipelines.
Open-source, cross-agent Agent Skills for DevOps, DevSecOps, Cloud, Kubernetes/platform engineering, CI/CD tooling, GitOps/Argo, policy, security scanning, SRE, standards/compliance, MLOps, AgentOps, and enterprise collaboration. Build once, use in Claude Code, GitHub Copilot, OpenAI Codex, Cursor and Gemini CLI.
Curated list of open-source LLMOps tools: tracing, evals, AI gateways, guardrails and prompt management. Sorted by stars, refreshed weekly.
Proxima lets existing GPUs serve 4x more concurrent requests
⚖️ Kadı — a calibrated judge in front of your frontier LLM. Routine decisions answered locally with a conformal-prediction guarantee (≤ α disagreement with the oracle); everything else escalated and learned from. Zero-dependency Python.