From "summarize this video" to a real research workflow

Most "AI video summary" tools just read the title and description. This one

fetches the actual spoken transcript and summarizes what was genuinely said —

which matters most for long videos like podcasts, lectures, and reviews where

the description tells you almost nothing. When a video has no captions at all,

it falls back to downloading the audio and transcribing it directly, so even

caption-free videos can still be summarized.

Reading the room, not just the script

A video's comment section is often where the most honest information lives —

the complaints, the "I bought this and here's what happened six months later,"

the corrections the creator never mentioned. The tool reads and analyzes those

comments, surfacing real audience sentiment alongside the video's own content.

Searches that correct themselves

A plain keyword search often pulls irrelevant results. This tool adds a layer

of judgment: after searching, it evaluates whether the results actually match

what you were looking for, and if they don't, it rewrites its own search query

and tries again — automatically, before bothering you with bad results. It

also shows its work, listing every query it tried and why, so the reasoning is

transparent rather than a black box.

A real example

Asked to research upgrading a sim-racing rig with a vague goal of "something

better," the tool refined its own search three times to filter out generic

driving-tutorial noise, then mined real owner comments to surface things no

single review mentioned: a possible quality-control inconsistency between

units, do-it-yourself reinforcement tricks owners actually use, a hidden cost

(the matching seat doubles the price), and two competing products recommended

by real owners — all in about two minutes.