Case Study:
Transforming Anti-Bribery & Corruption Training with
AI-Powered Content
Client
One of the leading distributors of medical aesthetics and advanced healthcare technology across the Middle East
Challenges
The client faced the significant task of converting a large volume of instructor-led training programs into digital learning modules within a tight timeline. The scale of content and the compressed delivery schedule made execution particularly demanding.
Another key requirement was ensuring high learner engagement. The client’s primary objective in transitioning to digital learning was to create more impactful and immersive training experiences.
Additionally, the client specifically requested that the courses avoid the use of 2D or 3D animations and stock footage. Instead, they wanted highly realistic content that closely reflected real-life workplace scenarios, ensuring authenticity and relevance for learners
Solution
AI-powered content development approach.
We designed a fully scenario-based digital training program that closely mirrored real-life workplace situations. Instead of relying on traditional 2D/3D animation or stock footage, we leveraged advanced AI tools to generate highly realistic, shot-by-shot visual content using carefully crafted prompts.
The environments were designed to reflect Middle Eastern settings, with characters representing local professionals. AI-generated voiceovers featuring regionally relevant accents and slang further enhanced authenticity.
Given the narrative format of the training, maintaining character consistency and scene continuity was critical. Our team ensured that the same characters appeared seamlessly across multiple scenes, preserving visual coherence throughout the course.
Result
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The project resulted in a first-of-its-kind AI-powered training program for Applebox.media, marking a significant milestone in our digital learning capabilities.
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The highly realistic, scenario-based approach enhanced learner immersion and engagement by closely replicating real-world situations.
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By leveraging multiple prompt specialists and advanced language models, we accelerated the development process delivering high-quality training content faster and more efficiently than traditional production methods.
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