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If you’ve ever tried to stitch together a clean replay from a multi-camera live stream, or compile course modules into a bingeable flow, or merge chapters for a premium OTT experience you already know how messy it gets.
You start with a few simple scripts. Then the edge cases creep in. One video has a different resolution. Another has a codec mismatch. Your team patches it with FFmpeg. It works in staging, breaks in prod. Now playback is jittery, timelines are off, and debugging means scrolling through log files at 2AM.
Why does something so basic feel so broken?
It’s not the feature that’s hard. It’s building it to work at scale, across devices, with consistent quality.
That’s why stitching is built into the core of FastPix. No glue code, no reprocessing pipelines. Just send the media parts we’ll return a playback-ready stream that’s optimized and built for production.
But before we show you how it works, let’s break down what video stitching actually is and why most traditional approaches fall short.
Stitching. Concatenation. Merging segments. Whatever you call it, the goal is the same: turn multiple video parts into one clean, uninterrupted stream.
And today, that’s not a bonus feature it’s how modern video products feel seamless.
Behind every replay reel, chaptered show, or course module is a team that had to piece together raw footage into a single file. For most teams, that still means downloading files, trimming clips manually, writing one-off FFmpeg scripts, and hoping the outputs behave on every device.
It’s slow. It’s brittle. And it doesn’t scale.
You fix one transition, only to find another mismatch between audio tracks. You clean up a resolution drift, and a frame boundary glitch shows up in Safari. What should be an automated step ends up living inside someone's editing software or buried in cron jobs and bash scripts.
This isn’t just a tooling problem. It’s an infrastructure gap. And for any platform delivering live content, VOD, or UGC, stitching has become part of the critical path.
If you’ve ever googled “how to merge videos,” chances are you landed on this:
1ffmpeg -f concat -safe 0 -i file_list.txt -c copy output.mp4
It looks simple and for a test clip or two, it works. But in real-world pipelines, this is where the problems start.
FFmpeg assumes everything is already aligned: codecs, resolutions, frame rates, aspect ratios, audio tracks, timecodes. The second any of that drifts, your merge either fails silently or produces a video with glitchy playback, broken sync, or incompatible metadata.
Here’s what teams typically run into:
Most teams build workarounds: transcode everything to a common format, normalize properties up front, and hard-code logic into batch jobs. But every fix adds latency and fragility.
FFmpeg is powerful. But it was never designed to be your stitching infrastructure at scale.
Which is why more developers now ask a better question: “Isn’t there a better way to handle this?”
Once you realize FFmpeg won’t scale, the next question is: Can this just be an API call?
Yes it can.
With FastPix, stitching isn’t a pipeline you build. It’s an endpoint you call. Whether you’re creating highlight reels, assembling personalized feeds, or combining branded intros and outros, you can stitch videos programmatically in just one request.
Here’s how it works.
You can stitch videos using either:
Create media from URL – for assets already uploaded or hosted on a public server Upload media from device – for direct client uploads Both methods let you define segments, control insert positions, and output a new stitched media asset.
You’ll define a base video and any number of additional segments. Segments can be inserted at exact timestamps (insertAt) or appended to the end (insertAtEnd). You must pick one or the other for each segment.
Example (stitching from URL):
1{
2 "inputs": [
3 {
4 "type": "video",
5 "url": "https://storage.fastpix.net/media/test/Lionking.mp4",
6 "segments": [
7 { "url": "https://.../clip1.mp4", "insertAt": 5 },
8 { "url": "https://.../clip2.mp4", "insertAt": 10 },
9 { "url": "https://.../clip3.mp4", "insertAtEnd": true }
10 ]
11 }
12 ],
13 "accessPolicy": "public",
14 "maxResolution": "1080p"
15}
Tip: Segment resolutions must match or be lower than the base video. FastPix doesn’t upscale. Frame rates should also be close to avoid jitter or sync issues.
If your base video is already uploaded to FastPix, you can reference it directly using a mediaId. Use the fp_mediaId:// prefix to target existing content.
json
"url": "fp_mediaId://7271d4de-e83c-431c-8aea-896c55f52645"
The output is a new stitched media object with its own media ID and playback IDs. The original file remains unchanged.
FastPix returns a new media asset with a unique ID and all the metadata you’d expect:
mediaId playbackIds status resolution metadata You can immediately stream the output via the provided playback ID.
Want to automate post-processing, analytics, or notifications?
Register a webhook for the event: video.media.splicing.ready
Sample payload:
1{
2 "type": "video.media.splicing.ready",
3 "object": {
4 "type": "media",
5 "id": "3be43075-58ea-4a81-9bf2-bbed98527f8c"
6 },
7 "status": "ready",
8 "data": {
9 "thumbnail": "https://images.fastpix.io/.../thumbnail.png",
10 "playbackIds": [ ... ]
11 }
12}
Once configured, your backend can dynamically stitch replays, UGC reels, or multi-part content with full control over placement, metadata, and output format. And everything scales with your traffic. If you try it out and want to know more, go through our Docs and Guides.
The challenge: Multi-camera streams create great coverage, but stitching those angles together after the stream ends usually means timeline juggling, syncing issues, and export delays.
The FastPix way: Pass the angle feeds to our API, and get a clean, single replay stream ready to publish in seconds.
The result: ESPN-style highlight replays without writing FFmpeg glue code or waiting on post-production.
The challenge: Viewers drop off between episodes, modules, or chapters especially when buffering kicks in or playback jumps between files.
The FastPix way: Pre-stitch entire seasons or course series into a seamless stream with adaptive bitrate playback.
The result: A binge-ready, Netflix-style viewing experience minus the buffering gap.
The challenge: Users upload in every format under the sun MOV, MP4, vertical, horizontal, 720p, 1080p. Manually normalizing and stitching that? A nightmare.
The FastPix way: Let the API handle it. FastPix auto-normalizes resolution and format so you can compile on the fly.
The result: TikTok-style highlight reels that feel curated, even when the inputs are chaos.
FastPix doesn’t just merge your videos it gets them ready for the real world.
Want to explore everything FastPix can do? Check out the features section for the full breakdown. Or jump in and try it yourself every new account gets $25 in free credits to start building.
Yes, but not all stitching APIs support this natively. Some platforms treat stitching as a low-level concat operation, while others (like FastPix) offer hooks for transitions, overlays, or branded intros/outros. If visual continuity is critical e.g., fade-ins or branded bumpers make sure your stitching solution allows for timeline-level control or layer-based editing during composition.
Audio mismatches different sample rates, channel layouts, or codecs can desync playback or cause dropped segments. Most traditional tools like FFmpeg require pre-normalizing audio before stitching. Production-grade solutions should detect and standardize these parameters automatically, or allow you to choose a dominant audio track to preserve.
It depends. Many stitching pipelines output a flat MP4, which isn’t compatible with ABR unless you post-process it into HLS/DASH. For real-time, scalable delivery, look for solutions that output stitched content directly into ABR renditions with playback-ready manifests especially for OTT or live-to-VOD workflows.
While both involve combining video parts, merging typically refers to simply appending files back-to-back. Stitching implies smarter composition handling timing, format mismatches, transitions, and even audio syncing. Stitching is preferred for production-grade workflows where playback quality and consistency matter.
To avoid quality loss, use a stitching tool that performs stream-level concatenation when possible and avoids re-encoding unless necessary. Solutions that support codec matching and ABR-ready outputs preserve visual fidelity better than tools that transcode everything by default.
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