Overview

With the production of hundreds of podcasts and content, the This Dot podcast collection has grown significantly, covering a wide range of topics. Social media and content teams have found it increasingly challenging to manually search these videos and extract valuable insights for engagement and promotion.

To address this, we developed an AI solution leveraging two specialized AI models alongside Retrieval-Augmented Generation (RAG) techniques, significantly reducing the time and effort required to search and extract useful information across our video content library.

Solution provided

Our AI-driven solution combines two distinct models: one for transcription and one for semantic search, enhanced with Retrieval-Augmented Generation (RAG) techniques.

Here’s how it works:

• Transcription Automation: First, each video is transcribed, converting spoken content into text with high accuracy. This creates a searchable text-based index for every video, providing a foundation for extracting key insights.

• Semantic Search and RAG Integration: To facilitate meaningful search, we implemented a semantic search model that understands context and intent. By applying RAG, the model retrieves relevant segments, enabling quick answers to complex queries rather than simple keyword matching.

• Easy Access and Scalability: Our solution is hosted internally, with a user-friendly interface where team members can quickly search videos by topic, keyword, or question. This allows anyone in the team to access insights quickly, regardless of their technical background.

Together, these elements form a powerful AI system that has transformed our video content from passive archives into an active, searchable resource, making it easier to share and leverage insights across teams.

Additional Use Cases

• Meeting Summarization: The AI could be enhanced to automatically generate concise summaries of team meetings, capturing key decisions, action items, and follow-ups. This would streamline communication, especially for team members who missed a meeting or want to review highlights without watching the entire recording.

• Interview Insights: The system could be applied to hiring interviews, making it easy to search through interview recordings to assess candidates based on specific qualities, skills, or responses. This would support more data-driven hiring decisions and allow interviewers to share valuable insights with the team efficiently.

• Advanced Content Summarization: Extending the summarization feature to podcasts and webinars, the AI could generate topic overviews and key takeaways, making it easier for the content and social media teams to create posts, recaps, and other promotional materials.

As we continue to develop this tool, these features offer the potential to further enhance productivity, improve communication, and streamline processes across any organization.