We’re evaluating tl;dv for company-wide async standups across our ~200-person team (mostly remote, some hybrid). The promise of AI summaries and clip-sharing for meetings sounds perfect for keeping everyone aligned without sitting through hours of recordings.
But I’m skeptical about scaling it to this size for a structured internal process. Most reviews I see are from small teams or for client calls. Has anyone actually rolled this out for 200+ users specifically for daily/weekly standups?
My main questions:
* **Meeting sprawl:** We’d have maybe 30+ simultaneous standup meetings across departments. Does tl;dv handle that many concurrent recordings/transcriptions reliably, or does it get laggy?
* **Clip overload:** If everyone starts making clips and sharing them internally, does the interface or notification system become unmanageable?
* **Integration depth:** We use Google Meet. The setup seems straightforward, but how well does the “summary” feature actually work for standup formats (quick updates, blockers, next steps)? Does it pick out action items consistently, or just generic meeting notes?
* **Admin controls:** At this user count, we’d need some central management. What’s the admin experience like for onboarding, usage reports, or managing subscriptions?
I’ve built a comparison spreadsheet (of course 😄) against other tools, but real-world scaling feedback is hard to find. Would love to hear from anyone running it at this scale—especially the pitfalls and how you structured the rollout.
Spreadsheets > marketing slides.
We piloted it for a 150-person engineering org last year for weekly syncs, and I can speak to your scaling questions directly.
On meeting sprawl, the concurrent recording limit wasn't the issue - we had about 25 meetings. The latency came in post-processing. The AI summaries for all those meetings would sometimes take 45+ minutes to generate after the meeting ended, which defeated the purpose for a quick standup update. The raw transcription was near instant, but the useful summary wasn't.
Your clip overload concern is valid. The notification system doesn't allow for granular team-based controls, so when people started clipping, it became a firehose. We ended up creating a separate Slack channel just for tl;dv notifications to avoid drowning the main channels. The interface itself gets clunky with more than a few dozen shared clips per week.
For standup formats specifically, the summary was hit or miss. It's good at generic "what was said" but poor at consistently extracting blockers or next steps unless someone literally says "my blocker is X". It won't infer an action item from "I'll look into that". For a true structured standup, we found it created more work verifying the summary than just reading a written update in Slack.
If you proceed, enforce a strict clip-sharing policy from day one and don't rely on the summary for action item tracking. Use it as a searchable transcript archive, not a source of truth.
Extract, transform, trust
Great to see this being tested at scale. I think user185 nailed the post-processing latency issue - we saw the same with summaries taking 30+ minutes for our 12-team daily syncs. The raw transcript is ready fast, but the AI summary isn't there when you need it for quick handoffs.
On your Google Meet integration question: the "summary" feature struggles with standup structure. It's decent for pulling generic talking points, but it often misses specific blockers or next steps unless someone says "my blocker is..." very explicitly. You'll likely still need to skim the transcript for the real action items.
For a 200-user shop, the lack of granular admin controls is the real deal-breaker. You can't easily segment clip notifications by team or project - it's pretty much all or nothing.
The latency issue user185 mentioned is spot on - we hit the same wall with AI summaries lagging for our 80-person product teams. It's ironic that an async standup tool forces you to wait almost an hour for the main feature you bought it for.
One extra nuance on your Google Meet integration question: the summary quality varies wildly based on how rigid your standup format is. If everyone follows the classic "yesterday/today/blockers" script, it's okay. If your team is more free-form, the summaries become useless. We ended up having to enforce a verbal template ("my blocker is...") just to make the AI picks reliable, which felt like tail-wagging-the-dog.
And yeah, the lack of admin controls is brutal at 200 users. You can't even bulk-disable the automatic "clip created" notifications per team. It's a notification storm waiting to happen.
Yeah, we tried exactly this rollout at 180 users last quarter. The concurrent meeting processing wasn't the lag issue, it was the post-meeting summary generation that became a bottleneck, just like others said. For a true standup, waiting 30-45 minutes for the AI digest kills the "async" benefit.
On your clip overload question, it's a real mess. The notification system is the problem, not the interface. You get a Slack ping for every single clip created across the entire company. We had to write a custom Zapier filter just to route them, because there's no native way to segment by team or project at that scale.
The Google Meet integration works fine technically, but the summary quality for standups is only good if you're extremely rigid. If your team doesn't literally say "My blocker is X," it often gets lost in generic notes. We ended up training our teams on a specific verbal format, which defeated the purpose of a natural conversation.
Another trial, another spreadsheet
That's a great point about training teams on a specific format. We had to do the same thing for our email marketing standups, just to get decent summaries.
Did you find the enforced structure made the standups themselves feel less useful? Like, did people start just going through the motions instead of having real conversations?
Totally relate to the "tail-wagging-the-dog" feeling. We had to do the same rigid scripting for a pilot.
But I'm wondering, did that enforced structure create any new problems? Like, did people start just reading from a script and stop mentioning smaller, unexpected issues because it didn't fit the "yesterday/today/blockers" template? That's my worry 😅
That's a perceptive observation. In our case, the enforced structure did indeed create a secondary behavioral issue. People began treating the standup as a data-entry task rather than a conversation. The smaller, unexpected issues - the "oh, by the way" comments that often surface real friction - were almost entirely eliminated because they didn't fit the three-part template the AI was trained to parse. It created a false sense of completeness in the summaries. We had to establish a separate, informal "post-standup watercooler" segment for those unstructured updates, which rather defeated the purpose of the tool we were trying to implement.
Measure twice, cut once.