A massive amount of critical business knowledge is trapped inside video files. Think about all the recorded Teams meetings, training sessions, and internal presentations stored across your company’s SharePoint and OneDrive. When someone needs to find a specific piece of information, they are often forced to manually scrub through hours of footage, hoping to catch the right moment. This isn't just inefficient; it's a significant drain on productivity. You can watch the full demonstration here: https://youtu.be/ihfKd_RMv_8

The Precision Gap in Standard AI

The core problem is that video is not natively searchable in the way a text document is. While you can search for a file name, you can't ask a question and get an answer from inside the video. We saw this as a major operational bottleneck for data-heavy teams. The goal wasn't just to find the right video file but to locate the exact second a specific topic is discussed. To solve this, we didn't rely on generic transcription services. We built a system that indexes multiple layers of a video's content. We chose this approach because a simple transcript often misses the full context. Our logic was designed to capture not just the spoken words from voiceovers and subtitles but also to recognize and index text that appears visually on screen.

Building the Indexing and Retrieval Logic

The system works by processing each video file stored in a company's existing cloud environment, like SharePoint Online or OneDrive. It creates a detailed, time-stamped index of the content. When a user asks a question through the internal chatbot interface, the system doesn't just search a text file; it queries this multi-layered index. The key technical decision was to prioritize precision. Instead of a conversational response that summarizes an entire video, the system is built to return a direct link to the exact timestamp where the answer is located. This transforms a 40-minute meeting recording from a time commitment into an instant resource. New employees can find answers in old training videos without interrupting senior staff, and teams can reference key decisions from past meetings in seconds.

How It Works in Practice

The system is now live. It handles entire video archives and gives teams a way to instantly query their collective video knowledge. The team no longer has to deal with the frustration of re-watching long videos to find a single piece of information. The chatbot interface provides a simple, intuitive way to ask questions in natural language and receive a direct link to the relevant moment in the video. This approach has proven particularly valuable for onboarding, where new hires can self-serve answers from a library of past training sessions.