2Supported Content Sources
AI Agent Studio provides the following connectors:
- SharePoint Connector: Provides access to your files in Microsoft SharePoint.
- Web Crawler Connector: Provides access to the pages of a website.
- Custom Content Source Connector: Provides a content type of your design.
SharePoint Connector
The SharePoint Connector enables AI agents to securely discover, retrieve, summarize, and act on files stored across SharePoint sites.
Key Capabilities
It provides governed, real-time access to enterprise knowledge, protected by Content Intelligence security models.
- Secure, permission-aware content access
- Natural-language search and semantic retrieval
- Read and sync content to hybrid search index
- Support for multisite architectures
Web Crawler Connector
The Web Crawler Connector enables autonomous discovery, retrieval, and structured extraction of web content.
Key Capabilities
The web crawler navigates websites, follow links, respect crawl policies, and transform unstructured web data into machine-ready formats for downstream reasoning and automation. AI agents can use content ingested by the web crawler for RAG-type agents.
- Autonomous crawling
- Configurable scope control (domains, paths, depth, frequency)
- Intelligent content extraction (HTML, PDFs, etc.)
- Change detection and incremental updates
- Compliance-aware crawling (robots.txt, sitemap, rate limiting)
- Output normalization to text embeddings
- Enforce content visibility with Content Intelligence security models
Technical Details
- Designate content crawl via sitemap or starting URL and specify depth of crawl
- Supports basic form authentication
- Supports JavaScript navigation
Custom Content Source Connector
It provides a way to store and maintain content for use in AI agents.
Key Capabilities
Custom content sources provide a flexible way for users to define their own content schema and integrate business-specific data into AI agent workflows. These sources start empty and are designed to be populated dynamically through agent-driven (agentic) flows or direct human effort. AI agents can create, update, retrieve, or delete content programmatically as part of their automated processes.
This approach allows organizations to build tailored repositories, such as custom knowledge bases or data stores, directly from within AI workflows, ensuring content remains current and aligned with real-time operational needs.
- Custom Schema: Design content structures tailored to your needs, defining specific fields and metadata for any type of information.
- Life Cycle Management: Set start, review, and end dates to control when content becomes active, ensure regular updates, and retire outdated information.
- Visibility and Security: Manage access with robust permissions, ensuring only authorized users can view or modify content, supporting enterprise compliance.
- Lexical and Semantic Search: Quickly find information using keyword (lexical) or context-aware (semantic) search, enabling smarter and more relevant results in workflows.
Business Benefits and Use Cases
- Flexible Content Storage: Easily store and organize a variety of business information such as policy documents, historical records, or notes using custom templates and an optional user-friendly interface.
- Tailored Insights: Leverage business-specific data models for more relevant and actionable AI responses.
- Improved Productivity: Enable agents to access, update, and automate content management directly within workflows, reducing manual effort.
- Enhanced Compliance: Control access, manage life cycles, and maintain content accuracy for regulatory and operational requirements.
- Faster Decision-Making: Advanced search (lexical and semantic) helps surface critical information quickly.