Colossyan AI Video platform

Three questions to the project team

What was the particular challenge of the project from a UX point of view?
Designing a generative AI solution presents a unique UX challenge: how can we help users effectively express the output they want the AI to create? The more clearly users can describe their goals, the more relevant and valuable the AI-generated results will be.
Another key challenge was aligning the users’ mental model of how the AI works with its actual behavior. Video creation involves two layers of abstraction: the content layer and the visual layer. We had to go through several rounds of iteration to ensure the model delivered exactly what users expected—because “turn my document into a video” can mean many different things. As always, the devil is in the details.

What was your personal highlight in the development process? Was there an aha!-moment, was there a low point?
The big aha! moment came when we truly understood what users meant by “turn my document into a video.” For our users, the expectation was:
Content layer: Preserve the exact wording and structure of their uploaded document.
Visual layer: Apply a clean, on-brand visual style based on their company’s design guidelines.
Once we clarified this, we were able to adjust our AI model accordingly. This also had a direct impact on our UI: we introduced a document upload feature for content and a template selector for the visual layer.

Where do you see yourself and the project in the next five years?
We’re constantly exploring how AI can help learning and development professionals create more engaging and effective training content. Our focus now is on interactive AI-generated videos that drive deeper engagement—especially for critical topics like workplace safety. We aim to push the boundaries of what’s possible with AI in corporate learning.