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AIUseCaseHub
AIUseCaseHub started as a private collection of applied AI ideas and is now a public research product. It tracks real enterprise AI deployments, each record tied to one organization, one system, and one public source you can check yourself. On top of the record, Insights answers recurring questions such as where AI is actually deployed and how agentic enterprise AI has become, while Trends compares deployment momentum with what news sources are discussing.
- My role
- Creator, architect, and builder
- Started
- Updated
- Visibility
- Public
- Built with
- Azure · Microsoft Foundry · Cosmos DB · Vector search · Agentic scraping · MCP
- source-linked AI deployments
- 4,015
- recurring patterns identified
- 227
- news sources tracked for trends
- 282
Problem
Most AI use case lists are inspiration without evidence. Teams need to know who actually deployed what, with which technology, and with which reported outcome.
Solution
A searchable record of real deployments with source links, filters for industry, business function, and cloud provider, plus analysis views that recompute as new deployments arrive.
Architecture
An agentic web-scraping pipeline (discovery, extraction, review) feeds a Cosmos DB record with vector search. The web app, a developer API, and a hosted MCP server all read from the same source-linked dataset.
Lessons learned
Curation and provenance matter more than volume. A good use case library helps people decide what to build, and it has to show where every claim comes from.
More screenshots (3)
ai-use-cases · research · catalog · evidence