Meeting Recording vs Screen Recording vs Session Replay

The short version

	Meeting recording	Screen recording	Session replay
What it records	A conversation	A display or window	One user's interaction with one web app
Output	Audio, video, speaker-attributed transcript, participant metadata	A video file	A timestamped event log (DOM snapshots + mutations)
Does it have video?	Yes	Yes	No — it's reconstructed at playback
Who initiates it	A participant, or an automated recorder	The person doing the recording	The website owner, silently, for every sampled visitor
Who's the subject	Everyone on the call	Whatever the recorder points at	The visitor
Built for	Any product that needs meeting data, like notetakers, project management tools, healthcare scribes, and more	Tutorials, demos, bug reports, async video recording	Debugging, funnel analysis, UX research
Representative tools	Recall.ai	Loom, OBS, ScreenStudio	FullStory, LogRocket, Hotjar, PostHog, Sentry

What meeting recording actually captures

A complete meeting recording has four parts:

Microphone audio — the speech of the person recording
Outgoing app audio — audio from the meeting window
Video of the meeting window — participant tiles and screen shares
Meeting metadata — participant list, join and leave events, speaking events, meeting title and URL, and more

A meeting recording is only useful if it preserves who said what. That requirement is what separates it from the other two categories, and it's why meeting recording is far harder to build than it looks.

Meeting transcripts must first of all be diarized, with labels of who said which part. The catch is that systems try to infer speakers from a single mixed audio track, causing issues when people speak over each other or participants have similar voices.

Unlike other tools, Recall.ai avoids the guesswork by capturing separate audio streams per participant and transcribing each one independently. Because the streams are already isolated, attribution holds up even when multiple people talk at once, enabling what's called "perfect diarization" – diarization that's 100% accurate. Recall.ai then uses the participant list from the meeting to label transcripts with the actual names of each speaker in the meeting.

Many other meeting recording providers have no diarization capability, and even if they do, don't offer speaker names as labels. Without the ability to capture data like a participant list, even a diarized transcript will label people as "Speaker 1" and "Speaker 2." That significantly limits the usefulness of products built on top of this data: You can't route an action item, populate a CRM contact, or score a rep's talk ratio against an anonymous label.

What screen recording actually captures

Screen recording captures literally what's on someone's screen, similar to a tool like QuickTime Player or Loom. Usually, people use screen recording apps for things like tutorials, demos, and bug reports.

However, a screen recorder can't meet the requirements of meeting capture, leaving teams that rely on a screen capture API with gaps they have to work around.

For example, though Apple's ScreenCaptureKit API can capture all three media streams a meeting needs — screen, system audio, and microphone – it falls short of meeting recording.

Here are a few specific limitations:

It can't handle Picture-in-Picture. If you set it to window capture, the video will go black as soon as the user minimizes the call into Picture-in-Picture.
It records distracting content. If you set it to display capture, it will record the whole screen, including unrelated tabs, notifications, and whatever else the user does during the call. This can create distracting content and risks the user accidentally recording private content on their screen.
It doesn't separate speakers. All remote participants arrive mixed into one system audio stream. You'd have to create a separate workflow for diarization.
It doesn't know it's recording a meeting. You don't get information like participant names, meeting URL, and join and leave events, which are important for downstream workflows.

Final thoughts: Screen recording is a technique that meeting recording uses, but it is not a substitute for meeting recording.

What session replay actually captures

Session replay is the odd one out, and the most commonly misunderstood of the three.

It doesn't record video at all. A session replay library (most are built on the open-source rrweb) takes a snapshot of the page's DOM when the session starts, then records every subsequent change as a serialized diff: mutations, scroll positions, clicks, keystrokes, viewport changes. At playback, the player rebuilds the DOM from the snapshot and applies the diffs in order against a virtual timeline. What you're watching looks like a video but is actually live HTML, which is why you can open a replay and inspect elements in it the way you would in DevTools.

The architecture has real advantages for user research, including the fact that you get semantic information like which button was pressed and not just which pixels. However, while useful for understanding user activity, this approach doesn't capture audio or video directly and could not be used for meeting recording.

Which one do you need?

If your goal is…	Use	Why
An AI notetaker, meeting summaries, or action items	Meeting recording	You need speaker-attributed transcripts
Populating a CRM from customer calls	Meeting recording	Requires participant identity and meeting metadata
Sales coaching and talk-time analysis	Meeting recording	Depends on per-speaker timing
Analyzing past client conversations	Meeting recording	Needs a durable record with identity attached
A product demo or tutorial	Screen recording	Just need to record screen without being on a live call
An async video message to a colleague	Screen recording	Can quickly capture screen without being in a meeting
A bug report showing a visual glitch	Screen recording, or session replay if it's a web app	Replay adds console logs and network requests
Finding where users abandon a checkout flow	Session replay	You need aggregate, specific behavioral patterns
Debugging a production error with full context	Session replay	Ties DOM state to errors and network calls

Why meeting recording is the hard one to build

With meeting recording, the hard parts come from everything around making capture reliable, including:

Detecting that a meeting started, across platforms like Zoom, Microsoft Teams, and Google Meet, in a native app or any browser
Following the meeting window through tab switches and handling window minimization
Keeping microphone and outgoing app audio in sync when they arrive at different sample rates
Attributing speech to real names, which requires participant metadata the OS doesn't expose
Surviving a closed laptop, a dropped network, a dead battery
Doing all of it on two operating systems, across OS versions, without burning the user's battery

Where Recall.ai fits

Recall.ai is infrastructure for meeting recording. Its Desktop Recording SDK handles the list above as a managed layer: automatic meeting detection, window tracking that stays on the call, mute-state detection, and transcripts labeled with real participant names rather than "Speaker 1." It accounts for a wide variety of audio, video, and device edge cases, making it the most reliable option for meeting recording.

Where it isn't the answer: if you need tutorials or async video messages, use a screen recorder — Recall.ai doesn't compete with Loom or OBS, and you'd be paying for meeting infrastructure you don't need. If you need to know where users abandon your signup flow, use a session replay tool; Recall.ai has nothing to say about your DOM. But if you need reliable meeting recording infrastructure, Recall.ai is by far the best choice.