OpenText DAM (OTMM) - BRIA AI Integration and Automation

Common Integration Use Cases Between OpenText DAM (OTMM) and BRIA AI

1. AI-Generated Product Image Variations for E-commerce and Distribution Channels

Data flow: OpenText DAM (OTMM) ? BRIA AI ? OpenText DAM (OTMM)

Product teams can send approved master product images from OpenText DAM (OTMM) to BRIA AI to generate multiple commercial-ready variations with different backgrounds, settings, and contextual scenes. The resulting assets are returned to OpenText DAM (OTMM) with metadata such as product SKU, campaign, market, and usage rights, making them immediately available for e-commerce, marketplaces, and distributor portals.

• Reduces the need for repeated studio photography
• Speeds up creation of channel-specific imagery
• Improves consistency across product catalogs and sales channels

2. Campaign Asset Localization for Regional Marketing Teams

Data flow: OpenText DAM (OTMM) ? BRIA AI ? OpenText DAM (OTMM)

Marketing teams can use approved campaign visuals stored in OpenText DAM (OTMM) as source assets for BRIA AI to create localized versions for different regions, languages, and audience segments. For example, a single hero image can be adapted with different backgrounds, seasonal cues, or culturally relevant contexts while preserving brand standards.

• Supports faster regional campaign rollout
• Reduces dependency on external creative production
• Helps maintain brand control while enabling local adaptation

3. A/B Testing Asset Generation for Performance Marketing

Data flow: OpenText DAM (OTMM) ? BRIA AI ? OpenText DAM (OTMM) ? marketing platforms

Performance marketing teams can pull approved visuals from OpenText DAM (OTMM) into BRIA AI to generate multiple image variants for A/B testing. Variants can differ by background, composition, product placement, or lifestyle context. Once approved, the variants are stored back in OpenText DAM (OTMM) and distributed to ad platforms, email tools, or content management systems.

• Enables rapid testing of creative concepts
• Improves campaign optimization with more visual options
• Creates a controlled workflow for approved test assets

4. Automated Background Removal and Scene Replacement for Catalog Cleanup

Data flow: OpenText DAM (OTMM) ? BRIA AI ? OpenText DAM (OTMM)

When product photography arrives with inconsistent or outdated backgrounds, OpenText DAM (OTMM) can route those assets to BRIA AI for background removal, replacement, or enhancement. The cleaned and standardized images are then returned to OpenText DAM (OTMM) for use in product catalogs, web stores, and print materials.

• Standardizes large image libraries without manual retouching
• Improves visual consistency across product lines
• Reduces post-production workload for creative operations

5. AI-Assisted Asset Derivation for New Product Launches

Data flow: OpenText DAM (OTMM) ? BRIA AI ? OpenText DAM (OTMM)

For new product launches, OpenText DAM (OTMM) can provide reference images, packaging shots, or early product renders to BRIA AI to create launch-ready visuals before full photography is available. This helps marketing and sales teams prepare teaser content, pre-launch campaigns, and retailer materials earlier in the product lifecycle.

• Shortens time to market for launch communications
• Supports pre-release marketing with approved visual concepts
• Helps teams work ahead of final photography schedules

6. Museum and Heritage Collection Presentation Enhancements

Data flow: OpenText DAM (OTMM) ? BRIA AI ? OpenText DAM (OTMM)

Museums and heritage organizations can use OpenText DAM (OTMM) as the repository for collection images and video, then send selected assets to BRIA AI to create contextual presentation variants for exhibitions, educational materials, or digital storytelling. For example, artifact images can be placed into reconstructed environments or cleaned up for clearer public display while preserving the original master asset in OpenText DAM (OTMM).

• Improves public engagement with collection content
• Supports digital exhibition and education initiatives
• Maintains a governed master archive while enabling creative reuse

7. Controlled Creative Workflow for Asset Approval and Compliance

Data flow: Bi-directional between OpenText DAM (OTMM) and BRIA AI

OpenText DAM (OTMM) can act as the system of record for approved source assets, usage rights, and final deliverables, while BRIA AI handles image generation and manipulation. Bi-directional integration allows creative teams to submit requests from the DAM, receive generated outputs, and route them back for review, approval, and rights validation before publication.

• Creates a governed end-to-end creative workflow
• Supports auditability for commercial asset use
• Reduces risk of publishing unapproved AI-generated content

8. Scalable Content Production for Multi-Channel Marketing Operations

Data flow: OpenText DAM (OTMM) ? BRIA AI ? OpenText DAM (OTMM) ? downstream channels

Marketing operations teams can use OpenText DAM (OTMM) as the central asset hub and BRIA AI as the production engine for generating large volumes of channel-specific visuals. This is especially useful for social media, paid media, retail partner portals, email campaigns, and seasonal promotions where many variations are needed quickly.

• Increases content volume without proportional headcount growth
• Improves reuse of approved source assets
• Supports faster execution across multiple channels and teams