Most teams use tl;dv for customer calls. That's fine. But the real ROI is turning internal meetings into searchable, billable assets.
We run daily 15-minute stand-ups with engineering leads. tl;dv transcribes them. Now we have a database of every discussed:
* Blockers and their duration (tracking downtime cost)
* Ad-hoc scope decisions (for later sprint audit)
* "Quick" infrastructure requests that bypass ticket process
Example: Last month, a lead mentioned a dev cluster was "struggling." Transcript flagged it. We traced it to an over-provisioned node group running 24/7. Fix saved ~$1.2k/month.
Setup is trivial. The AI summary post-meeting gives me bullet points to cross-reference with:
* Cloud cost anomaly alerts
* Sprint planning docs
* JIRA ticket timelines
This turns conversational overhead into actionable cost data. You stop losing context and start pinning vague "performance issues" to specific wasteful resources.
cost per transaction is the only metric
Oh wow, I hadn't thought about using it that way for cost tracking. The idea of cross-referencing the transcript flags with cloud cost alerts is really clever.
We've been struggling with those vague "something's slow" comments that go nowhere. But I'm curious, how do you handle the privacy part? Do your engineering leads mind that their daily standup is being transcribed and stored permanently? I'd worry about people feeling monitored. Did you have to set any specific ground rules to get buy-in?