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Privacy Review

Do they own your data? Loom Privacy Policy Reviewed

Final Enterprise Readiness Rating: 6/10

⚠️ Partially ready (Reviewed 2026).

Area

Verdict

Notes

Data Residency & Storage

⚠️  Partial

References Trust Center for storage details but no specific data residency options mentioned in policy

AI Model Use

❌  High Risk

Uses AI for support responses and machine learning for various purposes but provides no transparency on models or enterprise controls

Data Minimization

⚠️  Partial

Collects broad categories of data including behavioral analytics and collaboration patterns

Privacy Controls

⚠️  Partial

Provides some opt-out mechanisms for marketing but limited granular controls for data processing

Compliance & Auditability

✅  Good

Has SOC 2, GDPR compliance, and Data Privacy Framework certification

Consent Handling

❌  High Risk

For a video recording platform, there's no mention of automatic consent workflows or recording notifications

Model Explainability

❌  High Risk

No information provided about AI model transparency, logging, or observability

Data Retention & Deletion

⚠️  Partial

Retention periods are described as 'reasonable' without specific timeframes, and some data persists after account deletion

Third-Party Sharing

⚠️  Partial

Shares data with global partner network and various service providers

⚠️ Recommendation for Enterprises:

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

  • Confidential client communications requiring recording consent
  • Healthcare data requiring HIPAA compliance
  • Financial services data with strict AI transparency requirements
  • Legal communications with attorney-client privilege

Instead, consider AI tools that:

  • Provide explicit data residency controls
  • Offer AI model transparency and bring-your-own-model options
  • Implement built-in consent workflows for recording
  • Support configurable data retention policies
  • Reduce third-party data sharing scope

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.

🔍  Loom Privacy Policy – Enterprise Risk Assessment

Audience: Security-conscious enterprise organizations evaluating Video messaging and screen recording platform for async communication for internal use in highly sensitive or regulated environments (e.g. legal, healthcare, finance, tech/IP-heavy orgs).

⚠️ Where Loom Falls Short – Critical Gaps

🔒  1. Data Residency & Storage

Quote: "For more information on where and how we store your information, please see the Atlassian Trust Center."

Risk: Enterprise clients in regulated industries need explicit data residency guarantees and on-premises deployment options for sensitive data

Enterprise Issue:

  • No explicit data residency options
  • No on-premises deployment mentioned
  • Storage details relegated to external documentation

Verdict: ⚠️ Vague on location controls

🧠  2. AI Model Use

Quote: "We may also use generative artificial intelligence in responding to your support related requests. Detection and response may leverage generative artificial intelligence or machine learning tools."

Risk: Enterprises need to know which AI models are used, where data is processed, and must have options to bring their own models or disable AI entirely

Enterprise Issue:

  • No disclosure of which AI models are used
  • No option to bring your own model
  • No way to disable AI processing
  • Unclear where AI processing occurs

Verdict: ❌ Opaque AI usage with no enterprise controls

📊  3. Data Minimization

Quote: "We also collect information about the teams and people you work with and how you work with them, like who you collaborate with and communicate with most frequently."

Risk: This level of workplace surveillance data creates compliance risks and employee privacy concerns in regulated industries

Enterprise Issue:

  • Collects detailed behavioral analytics
  • Monitors collaboration patterns
  • No clear way to limit data collection scope

Verdict: ⚠️ Extensive data collection with limited justification

⚙️  4. Privacy Controls

Quote: "You can control whether you receive these communications as described below at 'How to access and control your information' under 'Opt-out of communications.'"

Risk: Enterprise customers need workspace-level controls and admin settings to manage privacy at scale, not just individual user opt-outs

Enterprise Issue:

  • No workspace-level privacy controls
  • Limited admin settings for data processing
  • Opt-out focused rather than opt-in

Verdict: ⚠️ Basic opt-outs but lacks enterprise-grade controls

📦  5. Compliance & Auditability

Quote: "Atlassian, Inc. and its U.S. subsidiaries adhere to the Data Privacy Framework Principles regarding the collection, use, and retention of personal data that is transferred from the European Union and Switzerland to the U.S."

Risk: While compliance frameworks are solid, the policy doesn't mention audit trails or detailed logging capabilities that enterprises need

Enterprise Issue:

  • No mention of audit trails
  • Limited transparency on security monitoring
  • Compliance details scattered across multiple documents

Verdict: ✅ Strong compliance foundation

Risk: Video recording platforms need robust consent mechanisms to prevent legal liability in regulated industries with strict recording consent requirements

Enterprise Issue:

  • No mention of recording consent workflows
  • No automatic notification systems
  • Legal compliance burden placed entirely on customer

Verdict: ❌ No built-in consent workflows for video recording

🔍  7. Model Explainability

Risk: Regulated industries require full transparency into AI decision-making processes and audit trails for compliance and risk management

Enterprise Issue:

  • No AI decision logging
  • No model explainability features
  • No transparency into AI processing

Verdict: ❌ Zero transparency on AI operations

🧼  8. Data Retention & Deletion

Quote: "If your account is deactivated or disabled, some of your information and the content you have provided will remain in order to allow your team members or other users to make full use of the Services."

Risk: Enterprises need predictable data deletion schedules and complete data purging capabilities for regulatory compliance

Enterprise Issue:

  • Vague retention timeframes
  • Data persistence after account deletion
  • No configurable retention policies

Verdict: ⚠️ Vague retention periods with persistence issues

🤝  9. Third-Party Sharing

Quote: "We work with a global network of partners who provide consulting, implementation, training and other services around our products. We may disclose your information to these third parties in connection with their services."

Risk: Broad third-party data sharing creates additional compliance risks and reduces enterprise control over sensitive data

Enterprise Issue:

  • Extensive partner data sharing
  • Limited control over third-party processing
  • Potential for data sprawl across vendors

Verdict: ⚠️ Extensive partner ecosystem creates data sprawl

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

  • Strong compliance framework with SOC 2 and GDPR
  • Data Privacy Framework certification for EU transfers
  • Clear data subject rights implementation
  • Transparent about data collection practices
  • Provides data portability options

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.