Back office ops · Production

Stax saves a day or two per project with Otter automated meeting notes

The problem

Stax's consulting projects run only four to six weeks with significant setup time already consumed, leaving very little time for research and analysis; decentralised individual Otter accounts also created data governance and confidentiality risks.

First attempt

Microsoft Teams' built-in transcription was inadequate — not insightful, not interactive, and lacking the screenshot, annotation, and post-meeting review features consultants needed.

Workflow diagram · grounded in source
1
Meeting takes place
trigger
“Stax uses Otter for in-person and virtual meetings on Microsoft Teams and Zoom”
2
Real-time automated transcription
ai_action
“Otter's automated notes and insights can be used immediately”
3
Transcript enrichment
ai_action
“Otter's ability to enrich live meeting transcripts with images, comments, and other key insights”
4
Consultant annotation and review
human_review
“go back later and use the tool to highlight key words, phrases, and insights after the fact, without having to do a lot of typing or spend a lot of focus on the scribing of the meeting”
5
Action items and follow-up
output
“Stax can quickly get started on its corresponding action items and analysis”
Reported outcome

Otter saves Stax a day or two on compressed project timelines, delivers instant results compared to manual transcription services, and enables centralised data control through Otter Enterprise — reducing rogue account proliferation.

Reported metrics
Time saved per projecta day or two in a very compressed timeline
Transcription turnaround vs manual servicesinstant results
Reported stack
OtterOtter EnterpriseMicrosoft TeamsZoomGoogle Meet
Source
https://otter.ai/case-study/stax
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Otter saves Stax a day or two on compressed project timelines, delivers instant results compared to manual transcription services, and enables centralised data control through Otter Enterprise — reducing rogue account…

What tools did this team use?

Otter, Otter Enterprise, Microsoft Teams, Zoom, Google Meet.

What results were reported?

Time saved per project: a day or two in a very compressed timeline; Transcription turnaround vs manual services: instant results (source-reported, not independently verified).

What failed first in this deployment?

Microsoft Teams' built-in transcription was inadequate — not insightful, not interactive, and lacking the screenshot, annotation, and post-meeting review features consultants needed.

How is this back office ops AI workflow structured?

Meeting takes place → Real-time automated transcription → Transcript enrichment → Consultant annotation and review → Action items and follow-up.

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