30 SharePoint sites, thousands of documents, and no way to find what you need without knowing where it lives.
Casey Family Programs, the nation's largest operating foundation focused on foster care and child welfare, had documents spread across 30 SharePoint sites. Staff could not search across them effectively or securely. Armely built an Azure AI Search integration that made the full document library searchable from one interface.
Does this describe your SharePoint environment?
- Documents are spread across dozens of SharePoint sites with no unified search
- Finding a specific document means knowing which site it lives on first
- Built-in SharePoint search returns too many irrelevant results to be useful
- Some sites contain sensitive content that should not appear in general search results
- Staff spend time asking colleagues where things are instead of finding them directly
- There is no easy way to search document content, only titles and metadata
What Armely did for Casey Family Programs
Casey Family Programs is a national operating foundation based in Seattle, focused on reducing the need for foster care. Their document library spanned 30 SharePoint sites with no unified search or security-aware retrieval.
Armely integrated Azure AI Search with Casey's SharePoint environment. The solution indexes documents across all 30 sites, applies security trimming to exclude restricted content, and delivers semantic search results through a custom web interface built on Azure App Services.
Staff now search once and find what they need across the entire document library. Restricted content stays hidden from unauthorized users. The search interface surfaces relevant documents and links, not just titles.
At a glance
| Before | After |
|---|---|
| Documents spread across 30 SharePoint sites with no cross-site search | Azure AI Search indexes all 30 sites and returns results from a single query |
| Finding a document required knowing which site it was stored on | Staff search once and find documents regardless of which site holds them |
| Built-in search returned shallow, keyword-only matches | Semantic search surfaces contextually relevant documents and content |
| No way to exclude sensitive sites from general search results | Security trimming hides restricted content from unauthorized users automatically |
| No custom interface for document search and interaction | Custom web app on Azure App Services provides an intuitive search experience |
| Staff relied on colleagues or memory to locate documents | Self-service search reduces dependency on institutional knowledge |