About

Built for teams that process media at scale

Presentr Analyze is the media operations layer between content intake and structured delivery — combining AI analysis with reviewable results and automated pipeline workflows.

Our mission

Structured outputs from unstructured media

Every podcast episode, video recording, and audio file contains valuable structured information — transcripts, chapter markers, ad placements, speaker turns, and metadata — that teams currently extract manually or through fragile one-off scripts.

Presentr Analyze automates this extraction with AI-powered analysis pipelines that are repeatable, reviewable, and directly connected to your downstream delivery systems. The result is consistent, high-quality outputs without the operational overhead.

How we build

Principles behind the product

Repeatable over one-off
Every pipeline, template, and source configuration is designed to be reused. Process 1 file or 1,000 the same way.
Reviewable before delivery
AI results are a starting point. Human review, approval, and finalization are first-class steps in the workflow.
Transparent processing costs
Credits map directly to compute. Every run shows you exactly what features were processed and what they cost.
Delivery as part of the workflow
Processing without delivery is incomplete. Destinations are first-class objects connected directly to pipeline outputs.
Config over code
Media teams should not need engineers to change a pipeline. Everything is configured through the UI — no code deploys.
Observability by default
Every run, delivery, and pipeline event is logged. You always know what processed, what delivered, and what needs attention.
Technology

What powers Presentr Analyze

AI transcription
High-accuracy speech-to-text built for media content — handles multiple speakers, technical vocabulary, and noisy audio.
Ad marker detection
Identifies natural ad insertion points using acoustic and linguistic signals rather than manual timestamp entry.
Automated chaptering
Segments long-form content into titled chapters based on topic shifts, suitable for podcast chapters and video markers.
Translation
Multilingual output support for transcripts and subtitles across major languages with source-aware context.
Pipeline automation
A source-trigger → process → review → deliver workflow engine that executes the same way on every new asset.
Delivery integrations
Webhook, cloud storage, and API-based destinations with configurable payload formats and retry logic.
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