Otter.ai
Otter.ai is a meeting transcription assistant that joins Zoom, Meet, and Teams calls, produces live transcripts and summaries, and integrates with Salesforce, HubSpot, and Slack.
Risk score
Assessment across data handling, compliance, security and transparency.
Overview
Otter.ai (otter.ai) auto-joins calendar meetings via its OtterPilot agent, captures audio, and produces searchable transcripts, summaries, action items, and workflow outputs. It is SOC 2 Type II attested, certified under EU-US/UK-US/Swiss-US Data Privacy Frameworks for GDPR-grade transfers, and offers HIPAA compliance with BAA on the Enterprise plan. Enterprise risk centers on consent and scope: OtterPilot can auto-join any meeting on a user's calendar, recording confidential HR, legal, M&A, or customer conversations without all-party consent. Otter trains models on de-identified audio and transcriptions unless the user opts out via the transcript-rating flow. Business-tier and above support unlimited meetings; HIPAA requires Enterprise and an executed BAA.
Risk factors
3- Cloud-based service with third-party data handling
- Default training on meeting transcripts without clear opt-out
- Integration with other platforms may expose sensitive data
Recommendations
8- Disable OtterPilot auto-join and require explicit host consent per meeting
- Block personal Otter accounts on corporate domains; enforce SSO on Enterprise tier
- Require HIPAA BAA on Enterprise before any healthcare or PHI-bearing use
- Train staff on two-party/all-party consent laws and announce recording at meeting start
- Disable training opt-in by default via admin policy and user education
- Restrict Salesforce, HubSpot, and Slack integrations to approved channels
- Exclude HR, legal, board, and M&A meeting series from Otter calendar access
- Configure custom retention policy and review auto-join scope quarterly
Data handling
- Storage
- Audio, transcripts, and derived outputs stored on AWS US infrastructure; EU/UK/Swiss data transferred under Standard Contractual Clauses and Data Privacy Framework.
- Retention
- Retained as long as necessary for service purposes or legal obligations; custom retention policies available on paid plans.
- Training on inputs
- Models trained on de-identified audio and transcriptions; users may opt out by declining permission in the transcript-quality rating flow.
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