Case study · Vidable AI
Client project · AugmentProject period2023
Video intelligence
Implemented video-intelligence experiences that surfaced analyzed metadata including brand and sentiment analysis, topics, labels, people detection, and content summaries.
01
Why
A video library is hard to explore without structure.
02
Decision
Analyzed videos surface structured insights: brands, sentiment, topics, labels, people and summaries, built on Azure AI Video Indexer.
03
Alternatives considered
None.
04
What I built
Implemented functionality for presenting comprehensive insights derived from analyzed video content.
The platform surfaced multiple categories of video intelligence, including:
- Brand analysis
- Sentiment analysis
- Topics
- Labels
- People
- Content summarization
These insights allowed users to understand and explore video content through structured information rather than relying solely on manual video review.
05
Trade-offs
Azure AI Video Indexer has limitations. It gives a fixed set of capabilities, so we can't think outside the box and go beyond what it provides.
06
Outcome
Users can explore a video through structured information instead of reviewing it manually.
