Wedia - Google Document AI Integration and Automation

Common Integration Use Cases Between Wedia and Google Document AI

1. Automated extraction of metadata from incoming brand documents

Flow: Google Document AI ? Wedia

When teams upload contracts, product sheets, packaging specs, or campaign briefs into Google Document AI, the platform can extract key fields such as document type, product name, region, language, approval status, and expiration date. That structured metadata can then be pushed into Wedia to automatically classify and index the asset.

Business value: Reduces manual tagging, speeds up asset onboarding, and improves searchability and governance across global content libraries.

2. Intelligent ingestion of scanned or PDF-based creative assets into the DAM

Flow: Google Document AI ? Wedia

Marketing and operations teams often receive scanned PDFs, print-ready artwork, or supplier-submitted documents that are not machine-readable. Google Document AI can OCR and structure the content, then pass the extracted text and metadata to Wedia so the asset can be stored, tracked, and reused in the DAM with proper context.

Business value: Makes legacy and scan-based content discoverable, supports reuse, and reduces duplicate asset creation.

3. Compliance review support for regulated content

Flow: Wedia ? Google Document AI ? Wedia

For regulated industries such as healthcare, financial services, or consumer goods, Wedia can send content packages or supporting documents to Google Document AI for extraction of claims, disclaimers, dates, and approval references. The results can be written back to Wedia as compliance metadata or review flags before distribution.

Business value: Improves control over regulated assets, supports audit readiness, and helps teams identify content that needs reapproval before reuse.

4. Contract and rights management for digital assets

Flow: Google Document AI ? Wedia

Legal or procurement teams can process licensing agreements, talent releases, and usage-rights documents in Google Document AI. Key terms such as usage territory, channel restrictions, and expiration dates can be extracted and synchronized to Wedia, where they are attached to the relevant asset record.

Business value: Helps prevent unauthorized asset use, reduces legal risk, and gives marketers clear visibility into content rights and expiry windows.

5. Automated campaign brief enrichment and asset routing

Flow: Google Document AI ? Wedia

Campaign briefs submitted as PDFs or scanned forms can be processed by Google Document AI to extract campaign name, target market, product line, launch date, and required deliverables. Wedia can then use that structured data to route assets to the correct regional library, assign tags, and trigger downstream workflows.

Business value: Shortens campaign setup time, improves regional content organization, and reduces manual coordination between marketing operations and local teams.

6. Content performance analysis using document-derived context

Flow: Wedia ? Google Document AI ? Wedia

Wedia can send asset-related documents such as campaign reports, media plans, or distributor submissions to Google Document AI for extraction of performance-related data points. Those insights can be returned to Wedia and linked to the original asset record to enrich analytics and reporting.

Business value: Adds context to asset performance tracking, supports better content decisions, and helps teams understand which materials are being used in which markets.

7. Localization workflow for multilingual content packages

Flow: Wedia ? Google Document AI ? Wedia

When a master asset is prepared for localization, Wedia can send source documents to Google Document AI to extract text, tables, and structured elements for translation preparation. The processed output can be returned to Wedia to support versioning, regional adaptation, and approval workflows.

Business value: Accelerates localization, improves consistency across markets, and reduces the effort required to prepare content for translation and adaptation.

8. Automated archival and retention classification

Flow: Google Document AI ? Wedia

Google Document AI can analyze incoming documents to determine document type, retention category, and expiry-related information. Wedia can then use that metadata to apply retention rules, archive assets appropriately, or flag content for deletion or renewal review.

Business value: Strengthens content governance, supports records management policies, and reduces the risk of keeping outdated or noncompliant assets active.