Meeting analytics from raw data your product can trust

The metrics hiding inside every meeting

Meetings generate more measurable signal than almost any other workplace activity: who spoke and for how long, who got interrupted, who joined late, how many people sat silent, how much of the week a team spends in calls. Products that surface these patterns help teams run tighter meetings and give managers visibility they otherwise guess at.

The blocker has never been the analysis. It is getting clean, structured data out of Zoom, Google Meet, and Microsoft Teams in the first place, without maintaining bot infrastructure for three platforms.

Metadata you get without processing anything

Every meeting captured through MeetStream comes with structured metadata that powers a first generation of analytics before you touch a single audio frame.

• Full participant list for attendance and meeting-size analysis
• Join and leave times per participant, for punctuality and partial-attendance metrics
• Host identification, useful for analyzing who runs meetings and how
• Platform and duration, for meeting-load and tooling breakdowns

Talk time computed, not guessed

Per-participant audio is what separates real talk-time analytics from estimates. Because each speaker arrives as a separate stream and file, speaking duration, overlap, and interruption metrics are computed from ground truth rather than inferred from a mixed track.

Diarized transcripts layer language on top of timing: per-speaker word counts, question rates, topic distribution, and monologue detection. Together they support the metrics conversation and productivity products are differentiated by.

Start collecting with one request

Instrumenting a single meeting is a POST request with the meeting URL, no host permission or paid meeting plan required. For organization-wide analytics, calendar integration with Google and Outlook schedules bots across upcoming meetings automatically, up to three months ahead, and webhook notifications deliver events and data as each meeting completes.

From one meeting to organizational trends

Analytics gets interesting in aggregate. An event-driven pipeline drops each meeting's metadata and metrics into your warehouse as it ends, and trends fall out: meeting load per team, talk-time balance over quarters, attendance decay in recurring meetings. Because MP4 recordings and transcripts sit behind every data point, users can drill from a chart into the actual moment.

For teams with data governance requirements, bring-your-own S3 keeps media in your storage, and all data is encrypted in transit and at rest under GDPR-compliant, ISO 27001 certified practices. The bot is always a visible participant, which keeps measurement transparent to the people being measured.

How it works

1. Connect calendars or send a POST per meeting to place bots across the meetings you want to measure.
2. Receive metadata, per-participant audio, and diarized transcripts as each meeting ends.
3. Compute talk time, participation, and meeting-load metrics from per-speaker ground truth.
4. Aggregate into dashboards and let users drill down to the recording behind any number.

Frequently asked questions