Centric - Google Document AI Integration and Automation

Common Integration Use Cases Between Centric and Google Document AI

Centric is a product lifecycle management platform used by design-driven industries to manage product development, collaboration, and product data from concept to launch. Google Document AI extracts structured data from scanned documents, PDFs, forms, and other unstructured content using AI. Together, they can reduce manual document handling, improve data accuracy, and accelerate product development workflows.

1. Automated extraction of supplier specification sheets into Centric

Flow: Google Document AI to Centric

Supplier specification sheets, technical PDFs, and product detail documents can be processed by Google Document AI to extract key attributes such as dimensions, materials, compliance details, and packaging information. The structured data is then pushed into Centric to create or update product records.

Business value: Reduces manual data entry, speeds up onboarding of supplier content, and improves consistency in product master data.

2. Digitizing compliance and certification documents for product records

Flow: Google Document AI to Centric

Certificates of origin, test reports, safety declarations, and regulatory approvals can be scanned and parsed by Google Document AI. Extracted fields and document metadata can be attached to the relevant product, style, or component record in Centric for audit readiness and launch approval.

Business value: Improves compliance tracking, shortens approval cycles, and creates a searchable document trail for audits and market entry reviews.

3. Automating intake of line sheets and product catalogs from vendors

Flow: Google Document AI to Centric

Vendor line sheets and product catalogs often arrive as PDFs or image files with inconsistent formatting. Google Document AI can extract product names, SKUs, colorways, pricing, and availability, then map the data into Centric to support assortment planning and product setup.

Business value: Accelerates vendor onboarding and reduces errors caused by manual rekeying of catalog data.

4. Enriching Centric product records with data from purchase orders and invoices

Flow: Google Document AI to Centric

Purchase orders, invoices, and packing slips can be processed by Google Document AI to capture supplier, item, quantity, cost, and shipment details. This information can be matched to Centric product records to validate sourcing data and support product cost tracking.

Business value: Improves cost visibility, supports procurement reconciliation, and helps teams detect discrepancies earlier in the product lifecycle.

5. Capturing design approvals from annotated documents and forms

Flow: Google Document AI to Centric

Design review forms, signed approval sheets, and annotated PDFs can be digitized and extracted by Google Document AI. Approval status, reviewer names, dates, and comments can be written back to Centric to update workflow stages and maintain a formal approval history.

Business value: Streamlines stage-gate processes, reduces delays in signoff, and improves governance across design and merchandising teams.

6. Linking scanned product development documents to Centric project records

Flow: Google Document AI to Centric

Legacy documents such as tech packs, fit comments, lab reports, and handwritten notes can be digitized and indexed by Google Document AI. The extracted metadata can be used to classify and attach documents to the correct Centric project, style, or season.

Business value: Makes historical product information searchable, improves collaboration, and reduces time spent locating supporting documents.

7. Feeding structured product data from Centric into document generation workflows

Flow: Centric to Google Document AI

Centric can provide approved product attributes, descriptions, and compliance details to downstream document workflows where Google Document AI is used to validate or extract data from generated forms, declarations, or submission packets. This supports quality checks before documents are sent to suppliers, regulators, or internal stakeholders.

Business value: Helps ensure document accuracy, reduces rework, and supports controlled release of product information.

8. Bi-directional workflow for product launch documentation

Flow: Bi-directional between Centric and Google Document AI

Centric can serve as the system of record for product development, while Google Document AI processes incoming documents such as supplier submissions, compliance files, and launch checklists. Extracted data is written into Centric, and Centric can then trigger document generation or routing for review based on updated product status.

Business value: Creates an end-to-end digital workflow for product launch, improves cross-functional visibility, and reduces bottlenecks between design, sourcing, compliance, and operations teams.