Flect

Overview

Flect is an AI-powered podcast search tool that enables users to find specific spoken content within audio and video recordings using natural language queries. Unlike traditional keyword-based search engines that rely on metadata, Flect leverages OpenAI text embeddings to interpret the actual meaning of user searches, allowing for more precise and context-aware results.

One of Flect’s core functionalities is Deep Search, which enables users to locate exact moments in podcast episodes where relevant discussions occur. Instead of searching by episode titles or descriptions, users can describe what was said in their own words, and Flect will retrieve the corresponding timestamped segments. Each result is accompanied by a contextual preview, allowing users to assess its relevance before jumping directly to the desired moment.

The platform also includes smart filtering options, enabling users to refine searches by podcast name, video format, or time period. Playback can be adjusted for speed, and users can save searches, bookmark specific moments, and receive personalized recommendations based on their listening patterns.

Flect differentiates itself from conventional search engines and platforms like YouTube and Google by addressing their limitations in video content search. It provides high-speed, scalable indexing of millions of podcast clips with continuous updates. By offering a seamless and efficient way to search spoken content, Flect enhances accessibility and usability for researchers, podcast enthusiasts, and content creators.

Visit the Cracked AI Engineering blog https://www.crackedaiengineering.com to hear more about how I built Flect AI.