Paste a broadcast link, upload a recording, or connect a live channel and get clips during the stream itself. The AI marks the quotable passages, cuts each on a full sentence so nothing is truncated into something the speaker did not say, burns in captions, and grades every clip 0-100. No footage is generated. Every frame came from the source.
Real ClipSpeedAI output — every clip below was scored, cut, reframed to 9:16 and captioned automatically from the video above it.
Source video
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The workflow is built backwards from the deadline.
Paste the URL of the broadcast, hearing, presser or commentary episode, or upload the file if it never went online. If the event has not finished yet, connect the channel instead and clipping begins against the live feed. Paid plans handle files up to two hours, which covers most single programmes and a fair number of hearings.
The engine reads the transcript for the passages that stand alone as a statement — the admission, the number, the flat denial, the line that will be in everybody's headline by evening. Each becomes a clip bounded by complete sentences. That constraint is editorial as much as technical: half a sentence is a different claim from the whole one.
Sort by grade, read the caption track on anything containing a name, a figure or a date, and correct it if the transcriber misheard. Then publish or schedule to TikTok, Reels and Shorts. On a fast story the whole loop runs in minutes, which is the only speed at which a news clip is worth making.
News clipping is not a craft problem. It is a latency problem with an accuracy constraint attached.
Connect a YouTube, Twitch or Kick channel and clips are produced during the broadcast rather than after a replay finishes processing. When a press conference goes sideways at minute forty, the clip exists at minute forty-one. Most clipping tools cannot touch anything until the VOD lands, which on a breaking story is far too late.
A quote sliced mid-clause is the fastest way to earn a correction, and the damage is not repaired by a follow-up post. Cuts land at the start and end of sentences, so a speaker's qualifier travels with their claim instead of being lopped off by an automatic timestamp.
A three-hour hearing produces far more candidates than anyone can watch back. The 0-100 grade ranks them by how each opens and where its peak falls, which gives a producer a defensible order to review in rather than a scroll of thumbnails.
News clips are consumed on silent autoplay more than any other category. Word-by-word captions in eleven styles are rendered into the video itself, so nothing depends on a platform generating its own and nothing breaks when the file is re-uploaded elsewhere.
Two people arguing is the archetypal news clip and the archetypal reframing failure. Speaker tracking follows whoever holds the floor, and split-screen keeps both faces on when the interruption is the story. A fixed crop would sit on the desk between them.
Pressers are full of shuffling papers, microphone handovers and half-started questions. Silence and filler come out automatically, which compresses a rambling ninety seconds into a tight forty without altering a word of what was actually said.
There is no text-to-video, no synthetic voice, no AI-created imagery and no reconstruction in this product. Everything in an export originated in the file or stream you supplied. For anybody publishing news, that is not a limitation to apologise for — it is the only workable position.
Commentary that walks through a filing, a chart or a leaked memo needs the document legible, which a vertical crop destroys. The screenshare layout keeps the material whole with the presenter beneath it.
Connect TikTok, Instagram and YouTube and post without a download step in the middle. On a story with a two-hour half-life, removing the round trip through your desktop is a real gain rather than a convenience.
A developer API and an MCP connector mean the pipeline can run without a person clicking anything — a scheduled stream connects, clips arrive, a producer reviews. See the developer docs for the integration details.
A daily show is two hours of material that nobody outside your subscriber base will ever see unless it is cut down.
The social desk is usually one person against a full rundown. Automating the first pass leaves them time to judge rather than scrub.
Hearings and committee sessions run for hours and contain four minutes anyone will watch. Finding those four minutes is the job.
A rate decision or an earnings call has a very short window where reaction content travels, and it closes by the following morning.
Reaction is worthless the next day. Clipping a post-match presser live is the difference between leading the conversation and joining it.
Council meetings and regional pressers are under-covered precisely because clipping them by hand costs more than the story returns.
Everything about this category is downstream of one fact: attention on a story collapses fast. The same forty-five seconds that would have earned two hundred thousand views at nine in the morning earns four thousand at six in the evening, and it is not because the clip got worse. The audience already saw someone else post it.
Traditional editing workflows are structured for quality at the expense of latency. Somebody downloads the VOD, somebody scrubs it, somebody cuts and captions, somebody approves. Each step is reasonable and the sum of them is a clip that arrives after the moment. On a slow feature that is fine. On a breaking story it means you are permanently second.
The reason live clipping matters so much here, and matters less for a podcast or a course, is that it removes the largest fixed delay in the chain. You are not waiting for a broadcast to end, for a replay to process, or for a download to finish. The clip is being cut while the words are still being spoken.
Automatic clipping tools generally choose boundaries by energy in the waveform or by fixed duration, and both will happily start a clip in the middle of a subordinate clause. In most content that is merely ugly. In news it can invert a meaning: a speaker who said "if the report is accurate, then the minister lied" becomes a speaker who said "the minister lied".
Cutting on complete sentences is not a stylistic preference in that context, it is a guard rail. It does not make a clip fair on its own — you can still select a sentence that misrepresents an argument, and no software can stop you — but it removes the class of error where the tool itself manufactured a misquote while you were not looking.
The same applies to captions. A burned-in caption is a quotation on the record. Transcription is strong on ordinary speech and weak exactly where news is most exposed: surnames, place names, agency acronyms and spoken figures. Reading the caption before publishing takes fifteen seconds and prevents the kind of mistake that gets screenshotted.
It does not fact-check. It has no view on whether a claim in your footage is true, and it will grade a confident falsehood highly because confident delivery scores well. Verification is entirely your job and nothing about the interface should be read as implying otherwise.
It does not assess bias, tone or newsworthiness in any journalistic sense. The grade is about how a clip performs as a clip. Those are different questions and conflating them would be a serious mistake in this field.
It does not clear rights. Broadcast footage, wire video and another channel's stream all carry usage terms, and the tool has no knowledge of them. What you are permitted to republish is a legal question for you and your organisation.
And it generates nothing. No synthetic anchor, no AI narration, no illustrative footage invented to fill a gap. That is a deliberate product decision rather than a missing feature, and in news it is the decision that keeps the output defensible.
Publishing a figure straight off the caption track. Spoken numbers are where transcription breaks down most often, and a wrong figure burned into the frame cannot be quietly amended once the post is live.
Beginning the clip on the answer. Stripped of the question, a reply reads as a volunteered statement, and that is frequently a materially different thing from what happened. Dragging the in point back by one sentence costs nothing and removes the objection entirely.
Trusting a high grade on something you have not watched end to end. The score describes the shape of a clip and nothing about its substance, so a fluent, confident claim from a source you have not checked will sit near the top of your review list.
Clipping the reaction instead of the event. A commentator responding to a thing is nearly always weaker than the thing, and it goes stale considerably faster.
And leaving attribution to the post text. A clip separates from its caption within an hour of being posted, so anything identifying the speaker and the occasion needs to be inside the frame rather than underneath it.
Connect the channel before the event begins rather than during it. Streams that are already twenty minutes in can be joined, but you lose the earlier material, and on a presser the first ten minutes often contain the prepared statement everyone quotes.
Expect to review more than you use. A live feed produces candidates continuously, and the discipline is to look at the top of the graded list rather than everything. Two strong clips shipped in the first ten minutes beat eleven shipped after the news conference ends.
For a recorded programme where speed matters less — a weekly commentary episode, a long interview — the ordinary upload path is simpler and gives you a fuller set to choose from. The podcast clip generator covers that shape of content in more detail.
Most people frame this as a quality argument, and on any single clip the producer wins. They know the story, they know which sentence the rival outlet already used, and they know that the shrug fifteen seconds after the answer is the actual moment. No scoring model has that context. The comparison that matters on a news desk is not quality per clip, it is coverage per hour, and those are different measurements with different winners.
Say your Tuesday holds a two-hour committee session, a rate decision at midday and a post-match presser at eight in the evening. One person cutting by hand covers one of those properly and skims the other two. An automatic pass covers all three at a consistent standard, which frees the producer to spend forty minutes making the single clip that carries your masthead genuinely good rather than spending forty minutes scrubbing a timeline to find it.
The biggest mistake is treating those two modes as a choice. Run the automatic pass for breadth and the human pass for the piece you actually care about. Where the machine has no answer at all is intent: it cannot know that a minister's pause matters because of something said in a different hearing last month, and it will never grade that pause highly, because as a clip it is four seconds of silence.
There is also a category of work where hand-editing is not merely better but required. Anything with archive footage, a scripted voice track, a graphics package or a lower-third house style belongs in your own edit suite. Export a clean vertical from here and finish it there — the useful division of labour is that this end of the chain finds and cuts, and your suite decorates.
If the output is a package rather than a clip, stop here. A two-minute explainer with narration, stills and archive is an edit, not a selection problem, and nothing about automatic boundary detection helps you build one. The same applies to anything airing on broadcast, where the deliverable is a specific codec, a specific loudness target and a house graphics template.
It is also the wrong tool when you already know the exact moment. If you watched the segment live and you can name the timecode, opening the file and dragging two handles is faster than any automated pass, and it would be silly to pretend otherwise. Automation earns its place when the source is long, unwatched, or still running.
On alternatives: platform clip buttons on Twitch, Kick and YouTube are excellent for what they are, which is sharing a landscape link into a chat within seconds. A general video editor is the right answer for packages and for anything needing archive. A transcript search tool will find you a phrase across a season of programmes faster than a clipper will, and if your problem is really retrieval rather than production, that is the category to buy from.
And there is a hard boundary in the product itself: it does not fact-check, it does not clear rights, and it generates no footage. In practice, the desks that get the most out of it treat it as coverage insurance on the hours nobody has time to watch, then hand anything sensitive to a person before it leaves the building. If your bottleneck is verification rather than cutting, this fixes the wrong half of your day.
Observations from operating the pipeline in production — not general advice.
We audited finished clips against the audio instead of against the transcript, which is the only honest way to judge a boundary, and 71% of endings landed somewhere a listener would call wrong: mid-clause, mid-qualifier, mid-number. Rebuilding selection so a clip runs along a complete thought moved that same measurement to 17%. The uncomfortable detail for anyone auditing their own stack is that the better path already existed in the pipeline and had been left switched off, so the defect was configuration rather than code, and it was invisible from every dashboard we had.
Given a recorded programme, the engine reads the whole runtime before it commits to anything, so a moment forty minutes in is ranked against every other candidate in the file. Live, that comparison does not exist yet, because the rest of the press conference has not happened. The same event clipped live and clipped later from the replay will not produce an identical set, and it is worth knowing which one you want: the live set is shipped while the story is moving, and the replay set is better sorted.
Captions are rendered into the frame rather than shipped as a sidecar track, which is why they survive a re-upload to a third platform and cannot drift out of sync after somebody trims the file. The trade is that an error is permanent in every copy that has already travelled. Transcription is strongest on ordinary speech and weakest on surnames, agency acronyms and spoken figures — precisely the words a news clip gets judged on — so reading the caption track before publishing is the cheapest insurance in this entire workflow.
A skilled social producer makes better individual clips than any automatic system and will always be worth having. What they cannot do is watch a three-hour hearing and a live presser simultaneously. Use the tool for coverage and breadth, and the producer for the pieces going out under the masthead.
This is the default workflow and it is the one live clipping replaces. Between a broadcast ending and a replay being downloadable there is usually a gap of anywhere from ten minutes to an hour, and on a fast story that gap is the entire opportunity.
Platform clip buttons are quick and produce a landscape clip with no captions, no vertical reframe and no way to schedule it elsewhere. They are fine for sharing a link into a chat. They are not a production route for a channel that posts to three platforms.
Almost all of them require a finished file, which rules them out for anything happening right now. If your work is entirely retrospective analysis, judge instead on cut quality and on how the captions handle proper nouns. The honest test is one real broadcast — run one through.
The clearest test of this is a story you would have covered regardless. Clip it live, clip it by hand, and compare both the output and the clock.
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