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Data flow: Azure AI Document Intelligence ? Frontify
When teams receive brand briefs, packaging specs, legal approvals, or campaign documents in PDF or image format, Azure AI Document Intelligence can extract key fields such as document type, project name, region, product line, and approval status. That metadata can then be used to automatically file the document or associated asset in the correct Frontify workspace, brand portal, or folder structure. This reduces manual sorting and helps marketing and design teams find approved materials faster.
Data flow: Azure AI Document Intelligence ? Frontify
Organizations often manage brand approvals through scanned sign-off sheets, compliance checklists, or annotated PDFs. Azure AI Document Intelligence can capture approver names, dates, version numbers, and compliance notes from these documents and push the extracted information into Frontify as metadata or linked records. This creates a clearer audit trail for brand governance and makes it easier to verify which assets are approved for use.
Data flow: Azure AI Document Intelligence ? Frontify
External agencies and suppliers frequently submit packaging artwork, product sheets, or campaign collateral alongside specification documents. Azure AI Document Intelligence can extract SKU codes, campaign IDs, language variants, and market references from those documents, then route the related files into the appropriate Frontify brand library. This helps centralize external submissions and ensures assets are organized by brand, market, and campaign without manual intervention.
Data flow: Frontify ? Azure AI Document Intelligence
Frontify often contains authoritative brand structures such as product names, campaign names, region codes, approved terminology, and asset categories. That reference data can be sent to Azure AI Document Intelligence as lookup values or classification rules to improve extraction and document tagging. This is especially useful when processing large volumes of brand-related documents where consistent naming and categorization are critical.
Data flow: Bi-directional
Packaging teams can submit label proofs, dielines, or regulatory inserts to Azure AI Document Intelligence for field extraction, including ingredient statements, barcode references, and mandatory legal text. The extracted content can then be compared against approved brand guidelines and asset standards stored in Frontify. If mismatches are found, the workflow can flag the document for review before it is published or sent to print, reducing compliance and rework risk.
Data flow: Azure AI Document Intelligence ? Frontify
Many organizations still rely on legacy brand manuals, scanned style guides, or archived campaign documents that are not easily searchable. Azure AI Document Intelligence can extract text and structured data from these files, and the results can be stored in Frontify as enriched content or linked reference material. This makes older brand assets more accessible to global teams and supports faster reuse of approved content.
Data flow: Azure AI Document Intelligence ? Frontify
During campaign launches, teams often receive a mix of briefing documents, media plans, legal approvals, and localized content files. Azure AI Document Intelligence can extract launch dates, target markets, channels, and approval status from these documents, then trigger the placement of final assets into the correct Frontify campaign area. This improves launch coordination across marketing, legal, and design teams and helps ensure only approved materials are distributed.
Data flow: Azure AI Document Intelligence ? Frontify
For enterprises managing large volumes of brand assets, extracted metadata from invoices, release forms, usage rights documents, or content briefs can be synchronized into Frontify to enrich asset records. This can include rights expiration dates, usage restrictions, owner details, and market applicability. The result is stronger governance over which assets can be used, where they can be used, and when they need to be reviewed or retired.