Memory Podcasts // Your knowledge, out loud

Your AI sessions.
Turned into a podcast.
Listen anytime.

Everything you've worked on, researched, thought through, and captured — synthesised into a two-host conversation and rendered as audio on your machine. Put it on while you commute. Play it back before you return to a project. Your memory, always with you, even when you're not at a screen.

What it does // Audio from your own knowledge

Not a summary. A conversation about your work.

Celestos doesn't produce a robot reading your notes aloud. It synthesises your sessions, research, and memory into a two-host dialogue — one explains, one questions — so what you hear sounds like a real discussion about the work you've been doing. It makes your own knowledge easier to absorb than reading it.

Step 1 · You choose the source

Pick a project, a single session, a topic, or a bundle of files. Celestos reads everything you've fed it on that subject — notes, conversations, documents, voice memos, research.

Step 2 · Script is written

The local LLM synthesises the content into a two-host dialogue. Host A explains and recaps. Host B asks the questions a listener would ask. Timed to your chosen length.

Step 3 · Audio is rendered

The embedded ONNX TTS engine renders each speaker's lines with distinct voices. No cloud audio service. No API key. WAV output generated entirely on your machine.

Step 4 · It's yours forever

The file goes to your output folder. Listen in any audio player, AirDrop it to your phone, or queue it up for your commute. Regenerate whenever your project grows.

Use cases // Real requests, run end to end

Things people actually generate.

Turn my AI sessions from this week into a 10-minute podcast catch-up
Make a podcast from everything in my book project so I can listen back on my run
Generate a podcast briefing from my research project before I go into the client meeting
Turn all my notes about this startup idea into a 5-minute audio overview
Create a weekly recap podcast from my Sparks results and Hive outputs
Make a short podcast explaining what I know about this topic so I can share it with a colleague
Podcast options
Sources: Single session, full project, raw files, or a topic query
Length: Short (2 min) · Medium (5 min) · Long (15+ min)
Voices: Atlas (M) · Orion (M) · Nova (F) · Lyra (F) · and more
Format: Two-host dialogue or single narrator
Output: WAV file in your project output folder
> Turn my book project sessions from this month into a 10-minute catch-up podcast Reading 14 sessions · 3 documents · 8 voice memos Synthesising into two-host script... Rendering audio · Atlas + Nova voices ✓ Podcast ready — 9m 42s Saved: /output/book-project-catchup-2026-07.wav
Always remembering // Your knowledge follows you

Stay in context even when you're away from your desk.

Most AI tools lose you the moment you close the window. With Memory Podcasts, your project context travels with you as audio. Listen before a meeting to remember where you left off. Listen during a run to absorb a research thread. Your Celestos knowledge doesn't stay on your desk — it goes wherever you go.

Before you sit down

Generate a short catch-up from yesterday's sessions on your phone during your commute. By the time you open Celestos, you already know where you were.

Before a meeting

Ask for a 3-minute brief on a client project before you walk into the call. Celestos pulls from everything it knows about them and narrates it back to you.

Weekly knowledge recap

Set a Spark to auto-generate a Friday podcast from the week's AI sessions. Listen on the weekend. Stay on top of everything across all your projects without sitting down to review it.

Share your thinking

Generate a podcast from a project and send the WAV to a collaborator. They get your full context — the research, the decisions, the reasoning — in a format they can listen to on the go.

Privacy // Rendered entirely offline

Your conversations never reach a cloud audio service.

Every part of the pipeline — script generation, voice synthesis, audio rendering — runs on your machine using local models and the embedded ONNX TTS engine. Nothing leaves your device. No cloud API call. No third-party service processing your private sessions. Your knowledge stays yours.

Script: local LLM

The dialogue script is written by the same local model powering your chat. No external API call.

Voice: embedded ONNX TTS

Speech is synthesised by a built-in neural TTS engine running on-device. No ElevenLabs, no Google TTS, no cloud.

Output: local WAV file

The finished audio is a plain WAV file on your machine. Play it anywhere. Keep it forever. Delete it whenever you want.

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