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Data flow: Cloudinary to OpenText Decision Service
When new images or videos are uploaded to Cloudinary, metadata such as file type, dimensions, content tags, campaign name, or source channel can be sent to OpenText Decision Service to determine whether the asset can be approved automatically, requires manual review, or must be rejected. This is useful for marketing, legal, and compliance teams that need consistent enforcement of brand standards, regional regulations, or content restrictions before media is published.
Data flow: OpenText Decision Service to Cloudinary
OpenText Decision Service can evaluate customer segment, device type, geography, subscription tier, or order value and return the appropriate media delivery rule to Cloudinary. Cloudinary then serves the correct image or video variant, such as premium product imagery for high-value customers, localized visuals for specific markets, or lower-resolution assets for bandwidth-sensitive environments. This improves personalization while keeping decision logic outside the application code.
Data flow: Cloudinary to OpenText Decision Service
For e-commerce teams managing large product catalogs, Cloudinary can provide asset attributes such as background color, image quality, aspect ratio, and number of images per SKU. OpenText Decision Service can apply business rules to determine whether a product listing is ready to go live, needs additional images, or should be routed to merchandising for correction. This reduces manual catalog checks and helps maintain consistent product presentation across channels.
Data flow: Cloudinary to OpenText Decision Service, then to workflow or case management
When Cloudinary detects an exception such as failed upload validation, unsupported format, oversized video, or missing required metadata, the event can be passed to OpenText Decision Service to classify the issue and decide the next action. The decision service can route the case to the right team, such as creative operations, IT support, or compliance, based on severity, business unit, or asset type. This creates a structured exception-handling process instead of ad hoc email follow-up.
Data flow: OpenText Decision Service to Cloudinary
Global marketing teams often need different media assets by country, language, or regulatory market. OpenText Decision Service can evaluate campaign rules, market eligibility, and legal restrictions, then instruct Cloudinary which asset version to deliver. For example, it can ensure that a promotion video with a specific claim is only shown in approved regions, while Cloudinary handles the optimized delivery of the correct localized media file.
Data flow: Cloudinary to OpenText Decision Service
Organizations that accept user-uploaded images or videos can send Cloudinary asset metadata and AI-generated tags to OpenText Decision Service for moderation decisions. The rules engine can determine whether content is safe to publish, should be queued for human review, or must be blocked based on policy, user type, or content category. This is especially valuable for marketplaces, community platforms, and customer portals that need scalable moderation controls.
Data flow: Bi-directional
Cloudinary can provide usage data such as asset age, access frequency, campaign status, or last modified date to OpenText Decision Service. The decision engine can then determine whether an asset should remain active, be archived, or be deleted according to retention policies and business rules. In return, OpenText Decision Service can trigger Cloudinary actions to move assets into archive storage or remove obsolete versions, helping reduce storage costs and improve content governance.
Data flow: OpenText Decision Service to Cloudinary
Marketing operations teams can use OpenText Decision Service to decide which creative variant should be served based on campaign rules, audience attributes, or performance thresholds. Cloudinary then delivers the selected image or video version, including optimized formats and responsive renditions. This allows campaign managers to change media selection rules quickly without redeploying application code, improving agility in testing and optimization.