Dexa AI
Description
🖼️ Tool Name:
Dexa AI
🔖 Tool Category:
AI-powered conversational search engine; it falls under the category of Knowledge Base & Self-Service and Integrations & APIs, enabling users to interact with podcast and content databases using natural language.
✏️ What does this tool offer?
Dexa AI transforms how users explore podcasts and interviews by allowing them to ask questions in natural language and instantly get accurate answers linked to the exact timestamp in the audio or video source. It acts like a semantic search layer for spoken content — turning long conversations into searchable knowledge.
⭐ What does the tool actually deliver based on user experience?
• Converts spoken content (like podcasts and interviews) into an interactive knowledge base.
• Lets users search by meaning — not just keywords — across large libraries of episodes.
• Displays short, time-stamped answers with the ability to jump directly to that podcast moment.
• Offers curated discovery of trending topics and expert discussions.
• Integrates with podcast and video platforms for seamless data access.
• Delivers fast, high-quality semantic responses powered by advanced AI models.
🤖 Does it include automation?
Yes — Dexa automates the indexing, transcription, and semantic understanding of long-form audio and video content. It automatically extracts topics, entities, and time markers, updating its database as new episodes are published.
💰 Pricing Model:
Freemium (free basic access with premium tiers)
🆓 Free Plan Details:
• Free access to search and listen across a limited number of podcasts.
• Includes time-stamped AI summaries and short answers.
• Allows following certain creators or topics.
💳 Paid Plan Details:
• Premium plans unlock advanced analytics, unlimited searches, and early access to exclusive podcast datasets.
• Enterprise tier available for publishers and media companies seeking integration and analytics.
🧭 Access Method:
• Available via Web App at https://dexa.ai
• Integration with podcast platforms and APIs for embedding search experiences.
🔗 Experience Link: