Prompt

Are there any legal research platforms that keep client data private and do not train models on it?

Legal · Law Firms / Law firms1 observationLast seen Aug 3, 2026

Latest observation

Aug 3, 2026 · OpenAI APIWeb search: off

Yes. Some legal research and AI vendors say they do not use customer/client data to train their models, and many offer enterprise/privacy controls that keep your data isolated.

A few things to look for when evaluating platforms:

  • No training on customer data: The vendor explicitly states prompts, uploads, and outputs are not used for model training.
  • Data isolation / tenancy: Your data is logically separated from other customers.
  • Retention controls: Ability to set short retention periods or zero-retention options.
  • Encryption: In transit and at rest.
  • Access controls: SSO, role-based access, audit logs.
  • Contractual protections: DPA, SCCs, confidentiality terms, subprocessor list.
  • Jurisdictional controls: Data residency options if relevant.

Examples of vendors/products that have publicly emphasized privacy or no-training commitments in their legal AI offerings include:

  • Thomson Reuters / CoCounsel + Westlaw products: enterprise offerings typically come with contractual privacy protections; check the specific service terms.
  • LexisNexis / Lexis+ AI: enterprise/legal research offerings with privacy and no-training statements in some materials.
  • vLex / Vincent AI: enterprise-focused legal research with privacy controls; verify the current terms.
  • Harvey: enterprise legal AI platform; has publicly discussed not training on customer data by default, but confirm current terms.
  • Ironclad AI / legal workflow tools: some enterprise deployments offer no-training commitments, though they’re more contract workflow than research.
  • Microsoft Copilot for Microsoft 365 is not a legal research platform per se, but Microsoft states customer data is not used to train foundation models for those enterprise services.

Because policies change, the safest approach is to ask each vendor for:

  1. A written statement that your data will not be used to train models
  2. Their data retention policy
  3. A list of subprocessors
  4. Whether they support zero-retention / private deployment
  5. Their security addendum / DPA

If you want, I can help you make a vendor comparison checklist or draft a privacy questionnaire you can send to legal AI vendors.

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Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

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OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, and Meta AI.