AI Audio Production

Production-ready audio. Zero plugin chains.

Upload a raw recording. Get a broadcast-standard file back in under 8 minutes. Podvynt auto-levels, de-noises, removes filler words, and masters to your spec.

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How It Works

From raw recording to publish-ready in four steps.

  1. 01

    Upload or connect

    Drop files via dashboard, push via our API, or auto-pull from connected cloud storage (S3, Dropbox, Google Drive). Supports MP3, WAV, FLAC, M4A up to 4GB.

  2. 02

    AI processes your audio

    Our model classifies noise type, removes background hum and breath noise, balances multi-track host levels, and strips filler words — with no quality artifacts.

  3. 03

    Master to LUFS spec

    Choose -14 LUFS (Spotify standard), -16 LUFS (Apple Podcasts), or a custom target. Final limiter applied to prevent clipping. Metadata tags preserved.

  4. 04

    Retrieve and publish

    Download processed files, or push directly to Buzzsprout, Transistor, Libsyn, or Megaphone via our native connectors. Average processing time: 6 minutes for a 60-minute episode.

Features

Every audio tool your network needs, unified.

Adaptive noise reduction

Identifies and removes hum, HVAC noise, reverb, and background crowd noise without affecting voice clarity.

Multi-host level balancing

Up to 8 speaker channels per episode. Each voice balanced to the same perceived loudness so no host overpowers another.

Filler word removal

Detects and removes um, uh, like, you know, and custom-defined words. Transcript-aligned so timestamps stay accurate.

LUFS mastering

Integrated loudness normalization with configurable targets. True Peak limiter prevents clipping across all distribution channels.

Auto-transcription

Word-level transcript generated alongside audio. Speaker-diarized with confidence scores. Export SRT, VTT, or JSON.

Batch processing

Submit a full show backlog. Our pipeline scales horizontally — no queue delays even when processing hundreds of episodes simultaneously.

Technical Specs

Built for production-grade audio pipelines.

  • Formats: MP3, WAV, FLAC, M4A, OGG (export: MP3 or WAV)
  • File size limit: 4 GB per file
  • Speaker channels: Mono, stereo, up to 8-track
  • Processing latency: < 8 min for 60-min episode
  • LUFS targets: -14 (Spotify), -16 (Apple), -18 (YouTube), custom
  • Transcript output: SRT, VTT, JSON (word-level, speaker-diarized)
  • API: REST (async callbacks) + Webhooks
  • Storage: Processed files retained 30 days (Enterprise: 1 year)
API request 
POST /v1/productions
Content-Type: application/json
Authorization: Bearer pvnt_sk_...

{
  "source_url": "s3://my-bucket/ep42-raw.wav",
  "lufs_target": -14,
  "remove_fillers": true,
  "filler_words": ["um", "uh", "like"],
  "output_format": "mp3",
  "webhook_url": "https://yourapp.com/hooks/pvnt"
}

→ 201 Accepted: production_id "prod_abc123"

A note on what Podvynt does — and doesn't — replace. Our processing pipeline handles the mechanical work: leveling, noise suppression, filler removal, LUFS mastering. It does not replace a sound engineer's ear for narrative pacing, music bed decisions, or creative post-production choices. Think of Podvynt as handling the production floor so your audio team can focus on the creative layer.

Ready to cut post-production time by 60%?

Free trial. No card required. 14 days of full production access.

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