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Do they own your data? Granola.ai Privacy Policy Reviewed.

Final Enterprise Readiness Rating: 3/10

🧨 Not enterprise-ready (Reviewed 2025).

Area

Verdict

Notes

Data Residency & Storage

⚠️  Partial

US-only, AWS hosted; no EU region or on-prem/VPC options.

AI Model Use

❌  High Risk

External LLMs process your meeting data. No zero-trust option.

Data Minimization

⚠️  Partial

No audio retained, but transcripts kept unless deleted manually.

Privacy Controls

⚠️  Weak Default

Opt-out only for training; no workspace-level controls.

Compliance & Auditability

❌  Not Compliant

SOC 2 “in progress”; no ISO 27001, HIPAA, or industry certs.

Consent Handling

❌  User Burden

No built-in workflows or legal safeguards.

Model Explainability

❌  None

GPT-4/Claude used as black boxes; no observability or logs.

đź‘Ž Recommendation for Enterprises:

Do not adopt Granola in its current form if you handle:

  • Confidential client communications
  • Health, financial, legal, or regulated data
  • Sensitive IP or trade secrets

Instead, consider AI tools that:

  • Offer full control over data use
  • Allow bring-your-own model
  • Support SOC 2 Type II, HIPAA, GDPR, and configurable retention
  • Have consent automation and enterprise contracts ready

Better Alternative:

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

âś… Zero training on customer data

âś… You own your data. Fully opt-in privacy model.

🔍  Granola Privacy Policy – Enterprise Risk Assessment

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

⚠️ Where Granola Falls Short – Critical Gaps

đź”’ 1. Data Is Used for AI Training (Even After Account Deletion)

Quote: “We retain Aggregated Data in order to train our machine learning or artificial intelligence models and improving Granola’s products, software and services, including after termination of your account or the Services.”

Risk: Even though Granola states that data is aggregated and anonymized, enterprise organizations should not accept any reuse of their internal communications, especially for training AI models. The ability to opt out exists, but only for Enterprise customers and not by default.

Enterprise Issue:

  • Model training should be opt-in, not opt-out.
  • No proof is provided of effective anonymization (e.g. differential privacy, k-anonymity).
  • “Aggregated” may still leak patterns or sensitive context in edge cases.

Verdict: đźš« Risky default. Needs explicit opt-in, not vague opt-out via sales contact.

🧠 2. Third-Party LLMs Are Involved (OpenAI, Anthropic)

Quote: “We use best-in-class transcription providers such as Deepgram and AssemblyAI… For summarization, Granola employs advanced language models from top AI providers — specifically naming OpenAI and Anthropic…”

Risk: Granola sends your transcriptions and notes to external AI vendors (OpenAI, Anthropic). Even though Granola claims those vendors are contractually barred from training on your data, the lack of direct oversight over third-party model behavior (e.g., caching, inference leakage) makes this an unacceptable risk for highly regulated sectors.

Enterprise Issue:

  • No way to bring your own model.
  • No on-prem or VPC deployment.
  • No guarantees about model explainability or auditability.

Verdict: ⚠️ Serious risk for sensitive conversations. Unacceptable for regulated industries.

📦  3. No End-to-End Enterprise-Grade Compliance

Claimed: “Granola is working toward SOC 2 compliance”
Quote: “Granola takes a strong stance on privacy and security… aligning its data practices with GDPR requirements.”

Risk: “Working toward SOC 2” is not the same as having completed a Type II audit. There’s no mention of HIPAA, ISO 27001, CCPA, or industry-specific compliance frameworks. While encryption is claimed, there’s no audit trail or certification to confirm it’s implemented enterprise-grade.

Enterprise Issue:

  • No certification = no enterprise trust.
  • Vague “working toward” ≠ contractual assurances.

Verdict: ❌ Fails basic third-party compliance checklist.

🧼 4. No Audio Is Stored – but Transcripts Are Retained by Default

Quote: “Granola only keeps the text output after transcription… Notes are private by default (only shared if you choose).”

Risk: Granola does not store the audio — which is good — but it does store the full transcript, and you have to delete it yourself unless otherwise arranged. For enterprises with strict retention/deletion requirements, this is inadequate.

Enterprise Issue:

  • No retention configuration per workspace.
  • No automated data lifecycle enforcement.
  • Transcript retention after offboarding poses risk.

Verdict: ⚠️ Better than storing raw audio, but not sufficient for enterprise-grade data governance.

Quote: “Granola advises users to obtain consent from all meeting participants before transcribing… [we] tested a feature to post a consent notice in the video call chat.”

Risk: Granola puts legal compliance burden on the user, not the system. Enterprises need built-in consent workflows, audit logs, and policy enforcement. “Tested” consent messages don’t meet the bar.

Enterprise Issue:

  • No automated consent collection.
  • No proof of compliance workflow.
  • Legal liability remains on the customer.

Verdict: ❌ Fails duty-of-care for cross-jurisdictional consent handling.

âś…  What Granola Does Right (Credit Where It’s Due)

  • Anonymized training data only.
  • No audio recordings stored, only transcripts.
  • Data encrypted at rest and in transit on AWS.
  • Privacy-first UX: Notes are private by default, not auto-shared.
  • Clear, readable privacy policy with technical transparency.
  • LLM usage clearly disclosed, unlike many vendors.

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.