Is Granola AI safe? What local-first actually covers

Granola AI gets something important right that most of this category gets wrong: there is no bot in your participant list. If you have ever watched a client’s face change when “Otter.ai Notetaker has joined the meeting” appears on screen, you understand why that matters.

So the question is not whether Granola is careless. It is not. The question is what “local-first” covers and what it does not, because the phrase does a lot of work in this category and it means different things to different vendors.

Everything below is from Granola’s own published security documentation, checked 5 September 2026.

What Granola does on your machine

On desktop, Granola “accesses your microphone audio, and your meeting audio on your computer, and transcribes it.” No bot dials in. Nobody in the meeting sees a participant they did not invite.

Granola also states plainly that it “doesn’t store the audio from meetings.” That is a real commitment and it is better than the norm. Most cloud notetakers keep the recording indefinitely until you delete it, which is exactly the pile of material that gets breached or subpoenaed later.

On mobile, transcription happens after the meeting using temporarily cached audio.

What leaves your machine

Here is the part the phrase “local-first” tends to obscure. From Granola’s security page:

Granola uses best-in-class transcription providers (like Deepgram and Assembly) and AI providers (like OpenAI and Anthropic).

So the pipeline is: audio is captured on your computer, then sent to a transcription vendor to be turned into text, and that text is sent to a large language model vendor to be turned into notes. Local capture, remote processing.

Your notes and transcripts are then “stored in our US-hosted AWS Virtual Private Cloud,” encrypted at rest and in transit, with daily backups. Granola holds SOC 2 Type 2 and offers a GDPR data processing agreement.

That is a well built cloud product with a local capture step. It is not the same thing as processing that never leaves the device, and if your reason for wanting a private notetaker is that the words themselves are sensitive, the distinction is the entire point. Audio not being stored is good. The transcript is still the content.

The training question

Two statements from the same page, and they are easy to conflate:

1. “We do not allow third parties (like OpenAI or Anthropic) to use your data to train their AI models.”
2. “Granola trains on your anonymized data,” and users “can opt out.”

The first is about the vendors in the pipeline. The second is about Granola itself, and it is opt-out rather than opt-in for individual accounts. Enterprise accounts have model training turned off by default.

None of that is hidden. It is on their security page in plain language, which is more than many competitors manage. But “local-first” and “trains on your anonymised data by default” are both true at once, and most people reading the marketing would not predict the second from the first.

If you use Granola and this matters to you, the opt-out is worth finding.

So is it safe?

For most work, yes. If your meetings are internal standups, product discussions and customer calls that would be embarrassing rather than catastrophic to leak, Granola is a good product with a better than average privacy posture and a genuinely thoughtful no-bot design.

The calculus changes when the content itself is the risk. Privileged legal conversations. Patient sessions. Deal terms before announcement. Source conversations. In those cases what matters is not whether the vendor is trustworthy, it is that a transcript exists on someone else’s infrastructure at all. Trustworthy companies still receive subpoenas, get acquired, and change policies.

The narrower version of local

Private Notetaker runs the whole pipeline on your computer: capture, transcription, and the model that writes the summary. There is no transcription vendor and no LLM provider, because both models run on your machine. Turn off wifi and it still works, which is the practical test of the claim.

The honest costs of that, since this is a post about reading claims carefully:

• English only. Granola handles far more languages.
• Accuracy on hard audio is worse. Deepgram and AssemblyAI run much larger models on server hardware than anything that fits on a laptop. On a bad connection with crosstalk, cloud wins.
• No team features. No shared workspace, no cross-organisation search, no collaborative editing. Granola is better at all of it.
• Disk and battery. Roughly 640MB for the transcription model and around 4GB for the summarisation model, plus the CPU to run them.

That is the trade. It buys you one thing: there is no server side copy of your meetings anywhere, so there is nothing to breach, subpoena, or quietly re-purpose in a future policy update.

If that is the trade you want, here is the side by side comparison, and a wider list of Granola AI alternatives including tools that are not ours. If it is not, Granola is a good choice and you should find the training opt-out.

All Granola claims quoted from its published security documentation, checked 5 September 2026. Vendor policies change, so verify before relying on this.