Best GDPR-Compliant AI Meeting Assistants for European Teams

Residency is necessary and not sufficient. A vendor telling you data is hosted in Frankfurt has answered one question. The one that follows is who else touches it. If transcription or summarisation calls a model API hosted in the United States, personal data has left the EEA regardless of where the database sits, and you need a transfer mechanism for that leg. Ask for the subprocessor list, in writing, and read it. Jamie is unusually clear here, stating that data stays within the EEA, Switzerland, and the UK with limited subprocessor exceptions under standard safeguards. Most vendors are considerably vaguer, and vagueness at this stage of a procurement is itself information.

The training default is a purpose-limitation problem. Under GDPR you must specify why you are processing personal data and not quietly repurpose it. A vendor that transcribes your meeting to give you notes, and also uses that recording to improve its models, is processing for a second purpose that your participants almost certainly never agreed to. Otter.ai, Granola, and Notta all train on customer data by default, and in each case the opt-out is a setting the user has to go and find. Only Granola's Enterprise tier has it off from the start and enforceable by an administrator. In August 2026 a US federal court held that plaintiffs had plausibly alleged Otter was a third-party eavesdropper because it independently collects, retains, and uses recordings for its own commercial purposes — a pleading-stage holding in another jurisdiction, but the same underlying intuition about what repurposing does to a vendor's position.

Consent from one participant does not cover the room. This is the most common mistake we see in European deployments. The person who starts the recording can consent for themselves. They cannot consent on behalf of the client, the candidate, or the counterparty. Worse, for employee recordings consent is generally not a defensible lawful basis at all, because the power imbalance in an employment relationship means staff cannot refuse freely — so organisations relying on an employee consent form are usually relying on nothing. Bot-free tools sharpen this, because nothing announces itself and the disclosure duty falls entirely on your user. That is manageable with a stated practice. It is not manageable by accident.

The EU AI Act adds a prohibition that consent cannot cure. Article 5(1)(f) bans AI systems that infer employees' emotions from biometric data in the workplace. It has applied since February 2025, and the administrative fines behind it under Article 99 have been available since 2 August 2025, up to the higher of €35 million or 7% of worldwide turnover. 2 August 2026 brought general applicability of the Act's remaining obligations, not the penalty regime. The Commission's guidelines put emotion inferred from written text outside the prohibition, so most transcript-based sentiment scoring is likely fine; inference from vocal tone or prosody is much closer to the line. Tools that ship sentiment or engagement analytics — Read.ai, Avoma, Fireflies.ai — are the ones to ask, and the question is specifically whether the inference runs on audio or on text. Tools that simply do not score people, which includes every pick on this page, avoid the question entirely.