Does Grammarly Business train its models on my company's data?

Grammarly's enterprise terms, described on its Trust Center, state that business and enterprise customer content is not used to train Grammarly's general product models by default, and admins can review the specific contractual language for their plan. That commitment governs Grammarly's internal use of the data after it arrives. It does not change what the outbound request contained when it left the user's browser, which is the question a security team evaluating exposure actually needs answered.

Can our DLP tool block sensitive text from reaching Grammarly's API?

DLP tools typically inspect traffic at the network or endpoint layer, and many exempt HTTPS traffic to trusted SaaS domains like grammarly.com from deep inspection for performance reasons. Even where inspection is enabled, a generic DLP rule is unlikely to distinguish a routine grammar check from a generative rewrite request carrying a customer account number. Purpose-built policy enforcement on the AI request path addresses that gap directly.

Is disabling Grammarly's generative features enough to remove the risk?

It removes the risk specific to generative rewrite and compose calls, which tend to carry larger context windows. Grammarly's core grammar and tone suggestions still send the surrounding sentence to the cloud API for scoring, so turning off generative AI features narrows the exposure without eliminating the underlying pattern of text leaving the tenant for evaluation.

How is this different from a browser extension security review?

A browser extension review evaluates permissions, install method, and whether the extension can access more of the page than it needs. That review answers whether Grammarly should be allowed to run in the browser at all. It does not evaluate the content of the specific requests the extension sends once it is running, which is a request-level question that requires visibility into the outbound HTTP traffic itself.

Does Grammarly Business support single sign-on and role-based admin controls?

Yes. Grammarly Business supports SSO integration and admin roles for managing the account, according to Grammarly's support documentation. Those controls govern who can administer the Grammarly account and its settings. They do not evaluate, at the moment a suggestion is requested, whether the specific text in that request should have been sent to any external AI provider under the organization's own data policy.

Should regulated industries avoid Grammarly's AI features entirely?

Not necessarily, but the decision should be based on what data classes are permitted to reach the feature, not a blanket ban. Grammarly Business's admin controls can restrict the product to approved domains or disable retention, which narrows exposure for lower-sensitivity use cases. Organizations handling regulated data typically still need a policy layer that evaluates individual requests, because admin-level restrictions apply account-wide rather than per document or per user context.

Grammarly Enterprise AI Security: What the API Call Actually Exposes

A Grammarly suggestion does not appear by magic inside the document you are editing. The extension takes the sentence you just typed, plus a window of surrounding text for context, and sends it as an HTTP request to Grammarly's cloud API. The API scores it against grammar, tone, and style models, and for generative features like rewrite and compose, an underlying language model drafts replacement text. That response comes back to your browser or desktop client, and the suggestion appears inline. The interesting security question is in that outbound request, not in the extension itself.

TL;DR

Grammarly Business is a browser extension, desktop app, or Office add-in, but the AI suggestion itself is generated by a cloud API call carrying the surrounding document text.
That outbound request can contain confidential business content, customer PII, or source code a developer pasted into a comment field, depending on what the user was writing when the suggestion fired.
Grammarly Business offers admin-level controls over this data, including an enterprise data-privacy policy, SOC 2 reporting, and account-level settings, but those controls apply to Grammarly's own handling, not to what an enforcement layer between the user and the API sees.
The browser-extension and local-integration mechanics are a separate, out-of-boundary concern for endpoint and DLP tooling.

The request that carries your document

Grammarly's core product model is sending text to the cloud for evaluation. According to Grammarly's Trust Center, the service processes the text a user is writing to generate suggestions, and enterprise customers get contractual terms governing how that processing works. The mechanism is consistent across surfaces: a Word add-in, a Gmail compose window, a Salesforce case note, or a raw text editor all route through the same category of outbound call once Grammarly's assistant is active in that field.

For the generative features, an assistant call fires whenever a user asks Grammarly to rewrite a paragraph, generate a reply, or adjust tone. The prompt behind that call is not just the sentence on screen. It is a slice of the surrounding document, because a language model needs context to produce a coherent rewrite. That is not a defect. It is how the feature has to work. The exposure it creates, though, is different in kind from a spell-check suggestion, because the payload can now include whatever sits in the paragraph above and below the cursor.

What actually leaves the building

Picture a product manager drafting a customer escalation email in Outlook with Grammarly's add-in active. The email references an account number, a contract renewal date, and a line the PM pasted from an internal Slack thread about a pricing exception. When she clicks "improve this paragraph," that entire block travels to Grammarly's API as part of the generation request. None of that content was meant to leave the company's tenant, and nothing about the button she clicked told her it would.

The same pattern applies to source code. A developer commenting a pull request description in a text box with Grammarly enabled can trigger a generative suggestion that carries a code snippet along with the surrounding prose. Grammarly's enterprise documentation describes admin controls for exactly this scenario: account-level policies that disable specific features, restrict Grammarly to approved domains, or turn off data retention for suggestion history. Those controls exist because Grammarly recognizes the exposure. What they do not do is inspect the request against the specific user's role, the sensitivity of the account number in that email, or a policy that says pricing exceptions cannot leave the CRM.

Local integration is a different problem

The browser extension, desktop client, and Office add-in are Grammarly's access path to the text in the first place. That access model raises its own questions: which browser permissions the extension holds, whether it is installed via managed deployment or self-service, and whether it can read fields outside the intended scope. Those are legitimate concerns, and they belong to endpoint management and DLP tooling, the same category of control that governs any browser extension with broad page access. A CASB or endpoint agent can flag or block the extension itself. It generally cannot inspect the content of the specific HTTP request the extension sends once it decides to call the API, because that call is TLS-encrypted and often exempted from proxy inspection for performance reasons.

I think most security teams evaluating Grammarly spend their review time on the extension's browser permissions and skip the request payload entirely, which reverses the review priority given that the payload is where the actual document content travels. That is my one real complaint about how this gets reviewed in practice.

Where admin controls stop

Grammarly Business's admin console lets an IT team manage seats, enforce style guides, and, per Grammarly's trust documentation, review the company's SOC 2 Type II report and data-handling commitments. Those controls are about Grammarly as a vendor: does it retain suggestion data, does it train models on customer content, does it meet a specific compliance framework. They do not answer a narrower, request-level question: for this specific user, with this role, was this specific paragraph of text permitted to leave the tenant at all.

That gap is the same one described in model guardrails are not a security control. A vendor's own safety and privacy settings operate inside that vendor's product boundary. They are not a substitute for policy enforcement that happens on the wire, before the request reaches the vendor, informed by the calling organization's own identity and data-classification rules rather than the vendor's default configuration.

The identity context Grammarly's API never sees

Grammarly's API authenticates the calling account and, in enterprise deployments, the individual seat. What it does not receive is the organization's own authorization context: whether this specific employee's role permits sharing this specific data classification with an external AI provider at all. That decision is entirely the calling application's responsibility, in this case a browser extension the user installed, and most organizations have no inline mechanism to evaluate it before the request leaves. The post-authentication gap describes this pattern generally: a user is authenticated to their laptop and their SSO session, but nothing evaluates the specific outbound AI request against that identity's actual permissions.

Why AI security must be inline makes the case that a decision made after the request has already left cannot prevent the exposure it is reviewing. Grammarly's suggestion history and admin logs are a record of what happened. They are not a control that stops a specific request before the API processes it. An enforcement point sitting between the user's session and the outbound call, evaluating the request against a zero-trust policy rather than trusting that the browser extension made the right call, closes that specific gap.

DeepInspect

Grammarly's generative features, and any similar cloud-based writing assistant, route through the same HTTP boundary DeepInspect is built to enforce: an authenticated user's request leaving toward an LLM-backed API. DeepInspect is inline on that path and evaluates each outbound request against the calling identity's role and the data classification of the content, before the request reaches Grammarly's API, rather than after the fact in a suggestion log.

This does not replace the endpoint and DLP controls that govern whether the extension should be installed at all, and it does not replace Grammarly Business's own admin console or its SOC 2 attestation. It is the layer between the two: a per-request, identity-bound decision and a signed audit record showing what left the tenant, when, and under whose policy.

If your team is running Grammarly Business alongside other AI writing tools and wants visibility into what those tools are actually sending, we can walk you through it. Book a technical deep dive at deepinspect.ai.