Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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An easy-to-use feature store. Optimized for time-series data.
Helps teams build, deploy, observe or operate machine-learning systems.
Cherry Studio helps build, test, automate, or manage AI agents, prompts, models, and API workflows.
Layer - Neural network inference from the command line, implemented in.
I work to bring AI into production. I write about AI system design.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Open-source tool that lets you package ML models in a standard, production-ready container.
Creates or edits images with generative models and visual controls.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Fast inference engine for Transformer models in C++.
Curated list of awesome vector search framework/engine, library, cloud service and research papers to vector similarity search.
Deep ML supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
AI chat platform for asking questions, coding, reasoning, and working with DeepSeek models.
DeepSpeed supports deploying, serving, monitoring, or operating AI and machine-learning systems.
MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.
Dify supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Docs helps build, test, automate, or manage AI agents, prompts, models, and API workflows.
Dominodatalab supports deploying, serving, monitoring, or operating AI and machine-learning systems.
A library for probabilistic modelling, inference, and criticism. Built on top of TensorFlow.
10x faster, cheaper, and better vector database.
Everything AI/ML supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Interactive reports to analyze ML models during validation or production monitoring.