Back office ops · Production

Recall.ai powers timeOS Smart Meeting Insights with reliable meeting recordings

The problem

timeOS needed accurate meeting recordings and transcripts to power their Smart Meeting Insights feature, but their self-built recorder produced poor sound quality and inaccurate transcripts while consuming engineering time that should have gone to core product development.

First attempt

timeOS's self-built recording solution under-delivered with poor sound quality and inaccurate transcripts, prompting user feedback that forced the team to seek an external solution.

Workflow diagram · grounded in source
1
Meeting on video platform
trigger
“captures meeting recordings for video conferences on Zoom, Google Meet, and Microsoft Teams”
2
Recall.ai bot captures recording
integration
“Recall.ai's meeting bot fetches high-quality recordings from video conferences to power timeOS's Smart Meeting Insights function”
3
Speaker classification
ai_action
“With better speaker classification and A/V quality, the transcripts were more accurate”
4
Transcript production
output
“timeOS has used the solution to seamlessly record meetings and produce transcripts”
5
Smart Meeting Insights
ai_action
“timeOS is an AI productivity tool that keeps you on task by capturing meetings, creating summaries, and providing insights at exactly the right time”
Reported outcome

Recall.ai delivered high-quality recordings with better speaker classification and A/V quality, producing more accurate transcripts and freeing the engineering team to build core product features, resulting in consistent product growth.

Reported metrics
Transcript accuracytranscripts were more accurate
Product growthconsistent growth in our product
Reported stack
Recall.aiZoomGoogle MeetMicrosoft Teams
Source
https://www.recall.ai/customers/timeos
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Recall.ai delivered high-quality recordings with better speaker classification and A/V quality, producing more accurate transcripts and freeing the engineering team to build core product features, resulting in consist…

What tools did this team use?

Recall.ai, Zoom, Google Meet, Microsoft Teams.

What results were reported?

Transcript accuracy: transcripts were more accurate; Product growth: consistent growth in our product (source-reported, not independently verified).

What failed first in this deployment?

timeOS's self-built recording solution under-delivered with poor sound quality and inaccurate transcripts, prompting user feedback that forced the team to seek an external solution.

How is this back office ops AI workflow structured?

Meeting on video platform → Recall.ai bot captures recording → Speaker classification → Transcript production → Smart Meeting Insights.