Does Otter AI Train on Your Data? Privacy and Enterprise Controls

Does Otter AI train on your data? Otter's privacy policy says it improves and monitors the service by training proprietary AI technology on de-identified audio recordings and on transcriptions, which may contain personal information. Otter's Enterprise page advertises an organization-level AI model training opt-out available through an account manager. That opt-out needs written verification. It also answers only the training question. Recording and transcription remain separate controls. Retention, sharing, access, and integration controls also remain separate.

TL;DR

• Otter says it trains proprietary AI technology on de-identified audio recordings and transcriptions that may contain personal information.
• Otter Enterprise advertises an organization-level AI model training opt-out arranged through an account manager.
• Otter's terms permit business uses of aggregated or de-identified data, including machine learning and training.
• A training opt-out leaves meeting capture and transcription decisions open. It also leaves retention and sharing decisions open. Access requires separate review.

Does Otter AI train on your data under its privacy policy

Otter's Privacy Policy, effective June 16, 2026, lists service improvement and monitoring among its processing purposes. The policy specifically includes training Otter's proprietary AI technology on de-identified audio recordings and on transcriptions. It adds that those transcriptions may contain personal information.

De-identification is stated for audio recordings in the cited passage, while the parenthetical warning attached to transcriptions acknowledges possible personal information. A buyer should avoid compressing both data types into the claim that all training material is anonymous. The policy supports a narrower statement: Otter describes de-identified audio training and transcription training, with potential personal information in transcripts.

The meeting itself makes the distinction visible. A laptop microphone captures voices while a transcript pane fills with names and customer objections. Project dates and quoted figures appear beside them. Removing an account identifier from audio does not erase those details from the words spoken.

Otter Enterprise offers a training opt-out

Otter's Enterprise product page lists an AI model training opt-out under its security and administrative controls. The page says organizations can keep their data out of AI model training and directs customers to contact an account manager to get started.

That is stronger than an inference from generic privacy language because Otter names an organization-level control. The public page does not provide the configuration steps or effective timing. It also does not specify the data categories or treatment of previously processed material. Enterprise buyers need those details in the order form and data-processing documentation, or in a written support response, before treating the control as active.

I would make training exclusion an acceptance criterion rather than a sales-call promise. The evidence packet should show the covered organization and activation date. It should identify the applicable data categories and treatment of historical recordings and transcripts. The packet should also name the person authorized to change the setting. The AI vendor due diligence questionnaire provides a place to capture those answers.

Otter's terms preserve aggregated-data uses

Otter's Terms of Service say the company may use and disclose aggregated or de-identified data derived from customer data or service use for business purposes. The listed purposes include machine learning and training. They also include industry analysis and benchmarking. Analytics is listed separately. Otter says that Aggregated Data will not identify the user.

An enterprise training opt-out may address organization content used in AI model training while contractual rights for aggregated or de-identified data continue under defined terms. Buyers should ask Otter to map the public opt-out to the relevant contract language and explain any surviving data use.

The terms also place responsibility on customers for the data they enter or supply, as well as data they access or use and applicable privacy obligations. That allocation makes meeting admission and recording policy an enterprise responsibility. The AI vendor risk management guide helps connect contract review to ongoing control ownership.

Meeting governance starts before transcription

Training is one downstream use. The first control decision occurs before Otter joins or records a meeting. The organization needs a rule for which meetings qualify and who can authorize capture. It also needs rules for participant notice and the data classes that bar transcription. Local recording-consent law and sector obligations require legal review in the relevant jurisdictions.

A useful approval distinguishes ordinary team meetings from restricted sessions. Board discussions and legal advice can contain restricted information. The same applies to incident response and personnel cases. Unreleased financial results and customer calls can also contain information that a general meeting assistant should never receive under a broad calendar integration. Keep the policy tied to named meeting classes instead of relying on employees to spot every sensitive sentence after recording starts.

Administrative controls should cover sharing defaults and external guests. They should also cover export rights and integrations, along with deletion and account offboarding. A training opt-out cannot repair an accidentally public transcript link or an overbroad integration token.

Evidence needs route and workspace details

The approval record should name the Otter workspace and plan. It should record the training setting and contract version. Add the retention rule and sharing policy, then identify enabled integrations and the account owner. Add the privacy-policy version date and the date an administrator last verified each setting. Preserve screenshots or exports instead of writing "Enterprise controls enabled" in a spreadsheet cell.

Reopen review when the plan changes or an acquisition alters terms. Reopen it again when the organization enables a new integration or Otter changes its privacy policy. A training setting can remain unchanged while another data path expands. The AI vendor risk assessment template covers classification and route evidence and should sit beside the vendor record.

For direct use of Otter's hosted service, provider and workspace controls own these decisions. If an enterprise builds a separate API workflow and routes eligible HTTP model traffic through a gateway, request policy can govern that customer-controlled path. The distinction prevents an API control from being presented as oversight of every hosted meeting.

DeepInspect

DeepInspect can inspect authenticated HTTP model requests that an enterprise deliberately routes through its gateway. It can classify the request content and enforce an approved destination and data policy. It then writes a per-decision record before the provider receives the traffic.

Otter's hosted meeting capture, transcription workspace, sharing, retention, and model-training processes sit outside that boundary. Provider settings and contractual assurance govern those surfaces. DeepInspect applies when a separate customer-controlled API route is intentionally placed behind its HTTP enforcement point. Book a technical deep dive at deepinspect.ai.