What is Klypra?

Okay, picture this: it's 1 AM, some streamer you follow just wrapped a 4-hour VOD, and you're scrubbing through it trying to find the ten seconds chat lost their minds over, hoping nobody else has already clipped and posted it before you. That's the exact problem Klypra was built to kill.

Klypra watches Twitch streams 24/7 (well, whichever ones you point it at), reads chat in real time, and the moment chat reacts, it clips it, edits it, and ships it straight to your phone. No VOD scrubbing, no racing other clippers, no editing software.

Here's the pipeline:

1. Watches — reads the Twitch chat like a real viewer and spots highlights and funny moments as they happen.

2. Clips — the moment a highlight is detected, it grabs the best recent seconds immediately.

3. Edits — reframes for short format, burns in subtitles, and cuts out dead silence.

4. Ships — delivers the finished clip to your phone and web dashboard, ready to post.

The clip already exists while the stream is still live. You could post the clip before the streamer even finishes their sentence.

How does it actually detect the good moments?

I know what you're thinking — "sure, it says it detects highlights, but how do I know it's not just clipping random chat noise?" Fair question. Let me walk you through the engine so you can trust it.

Real-time detection, not VOD review. Most clipping tools wait for the stream to end and then scan the VOD. Klypra does the opposite — a chat listener joins the channel's IRC chat like a bot account and reads every single message while the stream is still live. By the time the stream wraps up, the clips already exist.

It builds a chat baseline for every channel. Here's the smart part: Klypra doesn't use a fixed message-rate number. Instead, it builds a rolling baseline based on the median of the last several 5-minute snapshots (up to a 30-minute window). So as a chat naturally grows or calms down during a stream, the baseline adapts with it. A spike is flagged as a "candidate" when the current message rate crosses a multiple of that baseline.

Then every candidate gets scored on several signals at once, producing a moment score from 0 to 100:

• Velocity — how far above the baseline the chat climbed, and how suddenly.

• Emote density — how many messages are emote-heavy hype reactions versus plain conversation.

• Copypasta detection — when chat repeats the same message or emote combo back-to-back, it signals a shared reaction.

• Unique chatters — did the spike come from tons of different people, or just a couple of loud accounts?

Only spikes above your configured clip threshold turn into an actual clip request; everything else gets filtered out as noise.

What does the automatic editing actually do?

Raw clips are one thing. Clips that are actually post-ready are another. Here's where Klypra does the work a human editor would normally do — in just a few minutes, automatically.

Smart reframing. You get to choose 16 (horizontal) or 9 (vertical) output. Klypra detects where the facecam sits in the frame and reframes each clip around it, so the crop follows the streamer and gameplay instead of chopping off the wrong half of the screen. Your face stays in the shot, the action stays in the shot — exactly how a good vertical clip should look.

Subtitles timed to the word. Every clip gets transcribed automatically, and subtitles can be burned straight into the video — timed to the word, not just the sentence. Big difference for watch time. You've got several styles to pick from: a clean classic look, bold, highlight, MrBeast-style, and boxed variants, plus control over where subtitles sit on screen. Set a default for your whole account or override it per channel.

Silence removal. Dead pauses kill pacing. Klypra can optionally strip out silence and long gaps before delivery, keeping the clip tight. And here's why that matters: watch time is one of the strongest signals TikTok, Reels, and Shorts use to decide how far to push your video.

Here's the thing that surprised me — all of this editing stuff works on the free plan. Reframing, subtitles, silence removal, all of it. The only difference is a small Klypra watermark on free-tier clips.

Who is this for?

Clip channel owners running clipping operations across multiple streamers, this is the core use case. Point Klypra at a channel, let it watch, stop scrubbing VODs by hand.

Viewers and content farmers hoping to catch viral moments across many streams at once. Set it up, let it watch, collect the clips as they land.

Casual clippers on smaller channels. Because Klypra adapts its baseline to each chat, even smaller communities work well, just lower the threshold and it catches moments a big-stream threshold would miss.

Streamers who want their own highlights repurposed to TikTok without extra work are also covered, it's just not the primary use case Klypra is built around.

One honest note: the free plan monitors one channel at a time. That's actually perfect for testing — you get 50 clips a month to figure out if the detection quality matches your taste.

Pricing and plans

Money talk, no surprises. Let's break down exactly what's free and what's coming with the paid tiers.

Here's the honest breakdown of the three options:

A few things worth highlighting:

• The free plan is genuinely free — no credit card, no trial countdown, just €0 forever. You get one channel monitored, 50 clips a month, all subtitle styles. Perfect for testing.

• Paid plans keep your clips for 30 days (vs. 14 on free) and your daily/monthly clip counts scale with the tier.

• Klypra Pro is currently in early access via a waitlist. You can join for free, and here's the fun part — 50 random people get a free month when the Pro tier launches. Expected Pro perks: more channels at once, 24/7 auto-start, more subtitle options, and no watermark.

No fine print, no hidden credit card requirement. Start free, and upgrade whenever you're ready.

Common questions