# Agentic AI Landscape and Trends

A data-driven landscape and dataset of agentic AI and model infrastructure projects, tracking GitHub metadata and OpenRank vitality scores, produced by Ant Open Source and inclusionAI.

Agentic AI Landscape and Trends maps two infrastructure blocks: an Agent Infra block covering applications, frameworks, runtimes and tools, and a Model Infra block covering data, training, serving and deployment. It highlights the projects the maintainers consider most representative of each layer rather than attempting to list every project in the space.

The canonical dataset is a CSV file keyed by GitHub repository, carrying GitHub metadata such as forks, license, language and topics, OpenDigger vitality signals, and curation fields recording why a project is included, its landscape layer and section, and any selection caveat. Project vitality is measured with OpenRank rather than a project's raw popularity count, so activity from issues, pull requests, reviews and contributors is taken into account.

A Next.js web application reads the dataset directly to render the landscape site, and the repository also publishes dated landscape reports, project case studies, and automatically generated weekly snapshots of newly surfacing projects.

Website: https://insights.inclusion-ai.org/