Do they own your data? Avoma Privacy Policy Reviewed.

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Final Enterprise Readiness Rating: 5/10

⚠️ Partially ready (Reviewed 2026).

⚠️ Recommendation for Enterprises:

Adopt Avoma with caution. Be especially careful if you handle:

• Healthcare PHI requiring HIPAA
• Financial data requiring SOC 2 Type II
• Legal client communications requiring privilege protection
• Highly classified IP or trade secrets

Instead, consider AI tools that:

• Provide SOC 2 Type II and industry-specific compliance certifications
• Offer data residency controls and guaranteed geographic boundaries
• Include automated consent management for meeting participants
• Add AI transparency features and bring-your-own-model options
• Implement enterprise admin controls for workspace-level data governance

Better Alternative:

✅ BuildBetter.ai — GDPR, SOC 2 Type 2, and HIPAA compliant

✅ Zero training on customer data

✅ You own your data. Fully opt-in privacy model.

🔍  Avoma Privacy Policy – Enterprise Risk Assessment

Audience: Security-conscious enterprise organizations evaluating AI meeting assistant for note-taking, transcription, and coaching for internal use in highly sensitive or regulated environments (e.g. legal, healthcare, finance, tech/IP-heavy orgs).

⚠️ Where Avoma Falls Short – Critical Gaps

🔒  1. Data Residency & Storage

Quote: "We may store and process information in various sites throughout the globe, including in sites operated and maintained by cloud-based service providers. At any time, you may opt-out of such transfer by emailing a request to help@avoma.com."

Risk: Email-based opt-out is insufficient for regulated enterprises that need guaranteed data residency controls. Financial and healthcare companies cannot rely on manual processes for compliance.

Enterprise Issue:

• No guaranteed US-only or EU-only storage options
• Manual opt-out process insufficient for compliance
• Third-party cloud providers with unknown locations

Verdict: ❌ Unacceptable global data sprawl

🧠  2. AI Model Use

Quote: "Data obtained through Google Workspace APIs is used exclusively to provide and enhance the services requested by our users. We do not use this data to develop, improve, or train generalized AI or machine learning models."

Risk: While they commit to not training generalized models on Google Workspace data, there's no clarity on what AI models they use, whether data feeds external LLMs, or if enterprises can control AI processing of their sensitive meeting content.

Enterprise Issue:

• No disclosure of AI model providers
• No bring-your-own-model options
• Unclear if meeting data feeds external AI systems

Verdict: ❌ Zero transparency on AI processing

📊  3. Data Minimization

Quote: "When you use our Service to record, transcribe, analyze and share the recordings of web conferencing meetings and dialer phone calls and take notes for those meetings and calls, collectively Content, may contain personal information."

Risk: While collection is business-justified, meeting recordings can contain highly sensitive information. The policy doesn't address data minimization controls for different types of meetings or sensitivity levels.

Enterprise Issue:

• No granular controls for sensitive meeting types
• Broad analytics collection on user behavior
• No ability to limit data collection by meeting classification

Verdict: ⚠️ Broad collection with business justification

⚙️  4. Privacy Controls

Quote: "At any time, you may choose (opt out) whether your personal information is (i) to be disclosed to a third party, other than to third parties who act as our agents to perform tasks on our behalf and under our instructions, or (ii) to be used for a purpose that is materially different from the purposes for which it was originally collected"

Risk: Individual opt-out rights don't scale to enterprise needs. Companies need workspace-level controls and administrative oversight to manage employee data processing consistently.

Enterprise Issue:

• No workspace-level privacy controls
• No enterprise admin dashboard for data governance
• Individual-focused rather than organizational controls

Verdict: ⚠️ Basic individual controls, lacking enterprise administration

📦  5. Compliance & Auditability

Quote: "Avoma complies with the EU-US Data Privacy Framework (EU-U.S. DPF) and the UK Extension to the EU-U.S. DPF, and the Swiss-U.S. Data Privacy Framework (Swiss-U.S. DPF)as set forth by the US Department of Commerce. The Federal Trade Commission (FTC) has jurisdiction over our compliance with the EU-US Data Privacy Framework."

Risk: DPF certification is positive but insufficient for regulated industries. Healthcare, finance, and legal firms typically require SOC 2 Type II at minimum, with many needing HIPAA or industry-specific certifications.

Enterprise Issue:

• No SOC 2 Type II certification mentioned
• No HIPAA compliance for healthcare
• No industry-specific security frameworks

Verdict: ✅ Solid foundation with room for improvement

📬  6. Consent Handling

Risk: Meeting recording tools must handle multi-party consent automatically. The absence of built-in consent workflows puts the compliance burden entirely on customers, creating legal liability for enterprises.

Enterprise Issue:

• No automated consent collection for meeting participants
• No built-in recording notifications
• Compliance burden shifted entirely to customer

Verdict: ❌ Fails basic consent automation requirements

🔍  7. Model Explainability

Risk: Enterprises need visibility into how AI processes their meeting data, especially for regulated industries. Without explainability features, companies cannot audit or validate AI decisions on sensitive content.

Enterprise Issue:

• No AI decision logging
• No model explainability features
• Cannot audit AI processing of sensitive meetings

Verdict: ❌ Complete black box operation

🧼  8. Data Retention & Deletion

Quote: "We may need to keep personal information for as long as necessary to support the purposes of processing under this policy and for additional legitimate business purposes, for example, for record-keeping, for cyber-security management purposes, legal proceedings, and tax issues."

Risk: Vague retention language creates uncertainty for enterprises with specific data governance requirements. The broad 'legitimate business purposes' exception could override customer deletion requests.

Enterprise Issue:

• No specific retention periods defined
• Broad business purpose exceptions
• Unclear post-contract data handling

Verdict: ⚠️ Vague retention with business override

🤝  9. Third-Party Sharing

Quote: "We do not sell, share, rent or lease your personally identifiable information. Avoma may engage Sub-Processors to Process Personal Data on behalf of the Customer. Customer hereby provides Avoma with a general authorization to engage the Sub-Processors listed at https://trust.avoma.com/subprocessors"

Risk: Strong commitment against data selling with transparent subprocessor management. However, enterprises should review the subprocessor list for third-party risks and ensure all subprocessors meet their security requirements.

Enterprise Issue:

• Need to audit all subprocessors individually
• General authorization may not meet all enterprise approval processes
• Subprocessor changes may require contract amendments

Verdict: ✅ Transparent subprocessor management

✅ What Avoma Does Right (Credit Where It's Due)

• Strong DPF certification with FTC oversight
• Clear no-selling policy with transparent subprocessor management
• Proper data protection agreements with subprocessors
• Individual privacy rights implementation
• Dispute resolution process with third-party arbitration

Disclaimer: This evaluation is based solely on publicly available information and documentation. For formal enterprise vetting, always request a vendor's latest DPA, security whitepaper, and third-party audit reports.