AI Infrastructure & MLOps

Run sandboxes, task queues, and custom model inference with ultrafast boot times, instant autoscaling, and a developer experience that just works.

Activeloop provides infrastructure for continual learning and develops the Deeplake GPU database for agents.

The Deep Diamond library provides fast tensor and neural network computations in Clojure using native CPU and GPU routines.

Crowdsourced AI prompts are organized into modular task patterns by Fabric, an open-source framework.

KitOps packages and versions AI models, datasets, code, and configuration as OCI artifacts.

OpenMetadata provides data cataloging, discovery, quality, observability, governance, and lineage tools.

FlexML offers an easy to use and flexible automated machine learning library for Python.

CLIP-as-service provides scalable image and sentence embeddings, reasoning, and ranking with CLIP.

ClearML manages AI experiments, data, pipelines, orchestration, scheduling, and model serving in one MLOps platform.

Espresso AI uses machine learning to optimize Snowflake and Databricks data warehouses and reduce query and infrastructure costs.

The tensorflow-upstream repository provides a ROCm port of TensorFlow for the project.

ZenML provides a platform for machine learning pipelines and AI agents.

EigenCloud offers verifiable cloud infrastructure for building apps and AI agents, with a focus on trusted and accountable agent tasks.

Tensors and Dynamic neural networks in Python with strong GPU acceleration.

Developers can use Superexpert.AI to build and deploy multi-task AI agents on an open-source platform, with a downloadable project and live demo.

MLOps framework to package, deploy, monitor and manage thousands of production machine learning models.

Open-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.

Model deployment for AI applications is supported by nndeploy, a framework described as easy to use and high performance.

OpenLIT provides observability and evaluation for AI agents and coding agents, tracing models, tools, prompts, costs, and workflows.

Synexa AI deploys AI models through an API, with examples for image generation, video generation and image restoration.

Caffe provides an open framework for building and running deep learning models.

Notte provides cloud browser infrastructure and web automation for AI and coding agents.

Respan unifies LLM observability, evals, prompt optimization, and an AI gateway so teams can ship reliable AI applications.

Flower provides a federated AI framework for machine learning projects.