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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.

Helps teams build, deploy, observe or operate machine-learning systems.

Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.

Amadeus Code supports deploying, serving, monitoring, or operating AI and machine-learning systems.

Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.

MLOps in a notebook - uncover insights, surface problems, monitor, and fine tune your models.

Drop-in AsyncOpenAI replacement that transparently batches requests via the Batch API for cheaper LLM inference.

Awesome AI Web Search supports machine learning models, deployment, inspection, datasets, or AI development workflows.

Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis).

Inference hosting for AI teams who ship fast and scale faster.

Bayesian Inference Tools in Python.

An open-source LLM gateway with routing, load balancing, guardrails, and observability for 1000+ models. opensource.

Official inference framework for 1-bit LLMs, by Microsoft. opensource.

Deploy a ML inference service on a budget in less than 10 lines of code.

BurnRate supports deploying, serving, monitoring, or operating AI and machine-learning systems.

Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.

An easy-to-use feature store. Optimized for time-series data.

Helps teams build, deploy, observe or operate machine-learning systems.

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.

Open-source project that provides machine-learning models, research, training resources, or evaluation tools.

Deploy, manage, and scale machine learning models in production.