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Event Driven Orchestration & Scheduling Platform for Mission Critical Applications
Declarative Continuous Deployment for Kubernetes
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
☁️ Build multimodal AI applications with cloud-native stack
Open-source data movement for ELT pipelines and AI agents — from APIs, databases & files to warehouses, lakes, and AI applications. Both self-hosted and Cloud.
Always know what to expect from your data.
Always know what to expect from your data.
A cloud-native Pipeline resource.
🧙 Build, run, and manage data pipelines for integrating and transforming data.
🍴 Web applications made easy. Since 2011.
AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation
Machine Learning Pipelines for Kubeflow
Tired of pushing to test your .gitlab-ci.yml?
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
Kubernetes-native platform to run massively parallel data/streaming jobs
HuixiangDou: Overcoming Group Chat Scenarios with LLM-based Technical Assistance
A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow
A Julia machine learning framework
Data intensive science for everyone.
MLBox is a powerful Automated Machine Learning python library.
Tiny automation pipelines. Bring CI/CD to the smallest projects. Self-hosted, Lightweight, CLI only.
🪿 LinGoose is a Go framework for building awesome AI/LLM applications.
Easy pipelines for pandas DataFrames.
Find zero-days while you sleep. DeepZero is an automated vulnerability research framework that parses, decompiles, and analyzes thousands of Windows kernel drivers for exploitable IOCTLs natively using AI agents.
Pipeline Extension for Live Trading
BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.
AI team for Codex — researcher, PM, architect, developer, QA, and reviewer orchestrated through a configurable pipeline.
MCP Server for Spinnaker — manage applications, pipelines, and deployments via the Model Context Protocol