TasksBatchTools
Pricing
English
☰

Turn any recording into
a tight summary you can actually share.

audien·to is an AI audio tool that turns any meeting, interview, or talk into a tight summary — a one-paragraph TL;DR plus the 5–8 points worth remembering — in seconds. Unlike a full transcript you have to skim, it skips the filler and surfaces the substance. Free tier, 67 languages, no signup, audio auto-deleted in 72 hours.

Drop the audio in. We'll write a one-paragraph TL;DR and pull the 5–8 points worth remembering. Right length to skim, right depth to forward, no fluff.

● Record
Drop audio here
or click to choose a file · up to 2h · auto-deleted in 72h
LANGUAGE
required · 67 supported
What you'll get
  • TL;DR paragraph
  • Key points
  • Speaker attribution
Speakers auto-tagged. Tweak any section after upload from the Options panel — no setup needed up front.
The guide

Why a good summary is hard to write

Most summaries fail in the same two ways: they hedge (every point starts with “the speaker discussed…”) or they list (10 bullet points, no shape). Neither is what a busy reader needs.

A good summary leads with the thesis, names the 5–8 things worth remembering, and stops. It tells you whether to re-listen. It works as a Slack message or a paragraph in a wiki — both readers get the same answer.

What a good summary contains

  • TL;DR — one paragraph, ≤80 words, leading with the actual point — not a topic.
  • Key points — 5–8 bullets, each a complete claim a reader can act on.
  • Speaker attribution — who said what, when it matters (debate, interview).
  • No filler — no “the speakers discussed,” no “various topics were covered.”
  • Skim length — should fit on one screen — if it doesn't, it isn't a summary.

How audien·to summarises yours

What lands in the doc

  • TL;DR paragraphone tight paragraph, ≤80 words, leading with the answer or thesis — not a recap.
  • Key points5–8 bullets, each a single claim or decision. Ordered by importance, not chronology.
  • Speaker attributionadded when more than one speaker matters (interview, debate). Dropped for monologue.
  • Numbers preservedif a number was said (revenue, percent, deadline), it makes it into the summary verbatim.
  • No invented claimsif it wasn't in the audio, it's not in the summary. We summarise what was said, not what should have been.

Summary length & shape

  • Lead with the answeropen with the conclusion, not the topic. Readers came for the answer, not the agenda.
  • Bullets are claims“Pricing rose 12%” beats “Pricing was discussed.” Each bullet should be act-on-able.
  • 5–8 points, not 15if everything matters, nothing does. Pick the points worth remembering.
  • One screen, not twoa summary that needs scrolling has lost the plot.
  • Names and numbersconcrete details survive; vague references get dropped.

Knobs in the Options panel

  • LengthShort (3 bullets) · Standard (5–8) · Long (10+) — for the cases when 8 is genuinely too few.
  • ToneNeutral · Conversational · Punchy. Match the source audio.
  • Speaker attributionby name · by role · off — depending on whether speakers carry the meaning.
  • Bullet styleClaims (default) · Topics · Mixed — claims read fastest.
  • Output language23 supported. Useful for a meeting in one language, summary in another.
Why this works

Why modern AI hears what older tools missed

When you upload audio, two AIs go to work. The first one listens. It learned from millions of hours of real speech — accented, overlapping, full of “ums” and brand names that didn’t exist five years ago — so it can hear “Klaviyo,” “Substack,” or “the GPT pipeline” without flinching. The words older tools used to silently mangle come back right.

It hears in context. Instead of guessing one sound at a time, it takes in the whole sentence and uses everything around a tricky word to figure out what was actually said. That’s how a brand-new product name still lands correctly: the words around it tell the AI what kind of sentence it’s in.

And it cleans as it goes. Disfluency — “uh, like, I think… yeah” — doesn’t drop the rest of the sentence on the floor. Punctuation and capitalization come built in, so what you read is prose, not a wall of lowercase. By the time it hands off, the transcript already looks like what a careful typist would have given you.

What happens once we have your words

A raw transcript is the floor, not the ceiling. The second AI reads the whole document the way a careful editor would. It groups related discussion into chapters even when nobody says “moving on.” It surfaces the quote you’d actually screenshot — not the longest sentence on the page. It separates a decision from a tangent, an action item from a passing wish.

That’s the jump older tools couldn’t make: they gave you words, we give you shape. A meeting becomes minutes with owners, dates, and resolved questions. A podcast becomes show notes whose chapters track the real narrative, not the nearest five-minute mark. A voice memo becomes a send-ready email in your voice — not a list of fragments to stitch back together.

Each tool on this page is one of those pairings — the same listening AI up front, the same writing AI behind it, shaped for one specific output. You don’t pick. You don’t tweak. A thirty-second upload comes back as the thing you actually wanted, ready to use.