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Tyto by ai-coustics.

Catch audio problems before your AI agent does

Tyto analyzes audio streams in real-time to predict voice AI performance issues. Get instant scores on noise, reverb, loudness & more to prevent downstream failures.

Rank
▲ #34
Votes
101
Platform
Web / Mobile
Launched
Recently
Tyto by ai-coustics screenshot

More About Tyto by ai-coustics

Tyto by ai-coustics

Tyto is an advanced audio enhancement solution designed to clean and restore recorded speech content with exceptional precision. Built on the same audio intelligence foundation that powers real-time voice applications, Tyto transforms noisy, degraded recordings into clear, professional-grade audio perfect for post-production workflows, content creation, and archival restoration.

Product Highlights

  • Speech Restoration: Eliminate background noise, reverb, clipping, and compression artifacts from recorded audio while preserving natural voice characteristics and speaker identity.
  • Batch Processing: Process large volumes of audio files efficiently with automated workflows designed for content studios, podcast networks, and media production teams.
  • Studio-Grade Output: Deliver broadcast-quality results that meet professional audio standards for music, film, podcast, and video production environments.
  • Speaker Consistency: Maintain stable voice characteristics across processed clips, critical for voice cloning applications and multi-episode content series.

Use Cases

  • Podcast & Broadcast Production: Clean up remote interviews, field recordings, and imperfect studio captures to achieve consistent, polished sound across every episode.
  • Voice Dataset Preparation: Prepare training data for voice synthesis and AI voice cloning by standardizing acoustic quality across thousands of samples.
  • Archival Media Restoration: Recover historical recordings, legacy content, and degraded audio assets for preservation, redistribution, or remastering projects.

Target Audience

Tyto serves audio engineers, podcast producers, content creators, and machine learning teams who need to process recorded speech at scale without sacrificing quality or spending hours on manual cleanup.