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Curated list of the best truly open-source AI projects, models, tools, and infrastructure. Daily updated.
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Learn how to develop, deploy and iterate on production-grade ML applications.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Label Studio is a multi-type data labeling and annotation tool with standardized output format
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.
Workflow Engine for Kubernetes
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
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.
TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.
Always know what to expect from your data.
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.
Run, manage, and scale AI workloads on any AI infrastructure. Use one system to access & manage all AI compute (Kubernetes, Slurm, 20+ clouds, on-prem).
Build, Manage and Deploy AI/ML Systems
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Dynamic, resilient AI orchestration. Coordinate data, models, and compute as you build AI workflows.
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.
Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes
🐢 Open-Source Evaluation & Testing library for LLM Agents
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Machine Learning Pipelines for Kubeflow
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.
Maestro: Netflix’s Workflow Orchestrator
AI Infra / AI Orchestration / AI Control Plane
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.
OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.
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.
An open source DevOps tool from the CNCF for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI Artifact.