> Source: https://builder-docs.ema.ai/integrations-data/data-connectors > Title: Data Connectors # Data Connectors Ema grounds every answer in reliable, current information. Data connectors make this possible by synchronizing internal files -- tickets, policies, wikis, spreadsheets -- and, when needed, carefully selected public-web pages. Together they create a single, continuously refreshed knowledge base that every AI Employee can cite with confidence. ## File Ingestion Ema offers three options for bringing enterprise documents into the platform. Begin with one and expand as your needs grow. ### How Ema Brings Data In - **Local upload** -- Drag files onto the Canvas and validate parsing in seconds. - **Cloud-storage sync** -- Connect Google Drive, SharePoint, OneDrive, Box, or Dropbox. Ema keeps its data updated with the linked storage provider. - **Knowledge-base APIs** -- Link Confluence, ServiceNow, and similar platforms to keep wikis and runbooks fresh. The maximum per-file size supported for this ingestion type is 200 MB. All three paths feed a shared pipeline, so a bulk PDF import today and a SharePoint sync tomorrow do not require re-indexing. Knowledge Base APIs must be connected and authenticated from the **Integrations** page. Once connected, these connectors are available only from the **Shared Configuration** option. They are not available from specialized AI Employees like Recruiter or Document Generation. ### Knowledge Base Connector Scope Ema connects at the **knowledge base level** (or its equivalent in each platform), not at the instance or tenant level. When you connect a knowledge base, Ema ingests all content within it -- articles, folders, attachments, and nested categories -- automatically. Instance-level connections are not supported because they bypass access controls and segmentation, and introduce irrelevant content that degrades AI response quality. #### Terminology Across Connectors Connector Ema Connects At Higher Level (Not Supported) Confluence Space Site / Instance SharePoint Site Site Collection / Tenant Notion Teamspace or Database Workspace ServiceNow Knowledge Base Instance If you need content from multiple knowledge bases or spaces, connect each one individually through the Integrations page. ### File-Format Support Support Level Formats Production-ready PDF, DOCX, PPTX, TXT, HTML, MD Limited XLSB, CSV, XLSX, XML, JSON, very long PDFs with complex tables Unsupported Legacy Office binaries, source code, audio or video, native Google Docs/Sheets/Slides Scanned documents pass through OCR, but diagrams are not interpreted. Add captions when images matter. OCR capabilities are actively being improved. ### Preparing for a Connector Roll-out 1. Confirm every file is in a supported format. 2. Set up OAuth scopes or service-account keys with read-only access. 3. Test ten representative files to verify parsing quality and latency. 4. Estimate daily volume and adjust concurrency settings to prevent large syncs from interfering with other operations. ### What to Expect at Runtime - Markdown, HTML, and CSV files ingest almost instantly. - Office files and text-only PDFs take a few seconds per megabyte. - Image-heavy PDFs and media-rich presentations run three to four times slower. - Fully scanned documents require an additional OCR pass. ### Security Fundamentals The security architecture integrates OAuth 2.0 for cloud sources and service-account credentials for on-premises systems. All webhook callbacks are digitally signed. Connector dashboards clearly display rate limits, enabling you to prevent potential overloads. ### Known Limitations and Mitigations - **XLSB files** are partially supported. Consider exporting to XLSX format until native parsing becomes available. - **Very long PDFs with complex tables** may flatten. Consider splitting the PDF or converting tables to CSV format. - **No image-semantic extraction.** Include explanatory text adjacent to screenshots. ## Web Content Scraper Some business questions draw on information outside corporate systems -- partner portals, regulator updates, industry resources. The web content scraper captures this public content and folds it into the same index that serves internal documents. ### Purpose and Fit Common use cases where web scraping provides critical business value: - **Regulatory tracking** -- Compliance teams reference new agency guidance without manual copy-paste. - **Supply-chain status** -- Operations staff rely on carrier or supplier pages to predict delays. - **Investor messaging** -- Finance groups pull public FAQs and statements to prepare earnings-call answers. ### How the Scraper Works Capability Detail Crawl depth Follows links up to two levels from each seed URL Domain scope Stays on the source domain; external links are skipped except PDFs, which are always downloaded Content types Extracts HTML text and ingests any discovered PDF files Refresh Runs on demand; resubmit the URL list whenever needed ### Supported and Unsupported Sites Site Category Status Public static HTML Supported Pages with in-page PDF links Supported Light JavaScript sites Partially supported at two-level depth Password-protected, paywalled, CAPTCHA, heavy single-page apps Not supported in the current release ### Implementation Guidance - **Seed precisely** with targeted URLs (for example, `/support/faq`) rather than the main website homepage to keep crawl times predictable. - **Stage and validate** using a short list first; inspect parsed output in the dashboard, then widen scope. - **Plan runtime** because a two-level crawl can take several minutes; allocate processing windows accordingly. - **Re-crawl when needed** by submitting the URL list again whenever the source site posts significant updates. ## Connector-Specific Guides - [Confluence Data Connector](/legacy-docs/integrations-data/data-connectors/confluence)