OpenText Decision Service - Steg.ai Integration and Automation

Common Integration Use Cases Between OpenText Decision Service and Steg.ai

• Automated content approval for branded digital assets
  Steg.ai analyzes newly uploaded images, detects content type, and applies metadata tags. OpenText Decision Service evaluates business rules such as brand compliance, region-specific restrictions, and campaign eligibility. Approved assets are routed to the DAM or publishing workflow, while exceptions are sent to legal or marketing review. Data flow: Steg.ai to OpenText Decision Service.
• Rights-based asset protection and distribution control
  When Steg.ai identifies sensitive or premium content, OpenText Decision Service applies rules to determine who can access, download, or share the asset based on user role, geography, contract status, or license expiration. This helps prevent unauthorized use and supports controlled distribution across internal teams, agencies, and partners. Data flow: Steg.ai to OpenText Decision Service.
• Automated classification-driven workflow routing
  Steg.ai classifies incoming images by subject, format, or sensitivity. OpenText Decision Service uses those classifications to route assets into the correct workflow, such as product launch review, compliance approval, editorial review, or archival processing. This reduces manual triage and speeds up content operations. Data flow: Steg.ai to OpenText Decision Service.
• Exception handling for policy violations in asset libraries
  If Steg.ai detects missing tags, duplicate content, or potentially restricted imagery, OpenText Decision Service can trigger exception workflows, assign tasks to content stewards, and enforce remediation deadlines. This creates a controlled process for resolving content quality and policy issues before assets are published. Data flow: Steg.ai to OpenText Decision Service.
• Dynamic retention and archival decisions for digital assets
  Steg.ai provides content intelligence such as asset type, usage category, and sensitivity level. OpenText Decision Service applies retention rules to determine whether an asset should remain active, be archived, or be removed from circulation based on business policy, campaign lifecycle, or legal requirements. Data flow: Steg.ai to OpenText Decision Service.
• Automated tagging governance for enterprise DAM operations
  Steg.ai generates AI-based tags for images, while OpenText Decision Service validates whether those tags meet enterprise taxonomy standards, regulatory requirements, or campaign-specific naming conventions. Assets that fail validation are flagged for human review, improving metadata quality across the DAM. Data flow: Bi-directional, with Steg.ai supplying tags and OpenText Decision Service returning validation outcomes.
• Escalation workflow for high-risk or regulated content
  For assets containing regulated products, minors, medical imagery, or sensitive brand elements, Steg.ai identifies the content and OpenText Decision Service applies risk-based decision rules to escalate the asset to compliance, legal, or regional approvers. This supports faster review cycles while maintaining governance. Data flow: Steg.ai to OpenText Decision Service.