AI Search
Semantic search
Search that matches meaning across episodes so related ideas surface even without exact wording.
Backstory
Why this exists
Guests rephrase. Fans misremember titles. Semantic matching finds the idea behind the query.
How it helps
- Recover relevant episodes fans cannot name
- Improve ask quality
- Surface topical clusters
How it works
From setup to outcome
- 01
Embeddings capture passage meaning
- 02
Query matches nearest content
- 03
Results rank by relevance
Pros
- Better recall than keyword-only
- Works with natural questions
- Pairs with transcript search
Tradeoffs
- Occasional soft matches need human judgment
- Needs indexed content
- Very niche jargon may need exact search too
Related
Keep exploring
AI Search
Ask your podcast
Natural-language answers grounded in your transcript knowledge base.
AI Search
Full transcript search
Find phrases buried inside hours of audio.
AI Search
Cross-episode answers
Pull relevant moments from the whole catalog.
AI Search
Timestamp jump
Send people to the second where you answered them.
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