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New Reveal Report: 91% of eDiscovery Buyers Demand Private Deployment as AI Moves From Experiment to Operational Priority

AI-Assisted Document Review: Security & Data Privacy

Generative AI can accelerate document review, but only if legal teams can trust what happens to their data along the way. Reveal AI's AI-Assisted Document Review feature is woven directly into the Reveal Enterprise eDiscovery platform, giving reviewers a relevance rating and a narrative explanation for every document, without compromising on security. This white paper breaks down exactly how the feature works, where your data goes, and what protections are built in at every step.

Every query and response is encrypted in transit, using TLS 1.2/1.3 between Reveal Enterprise and the LLM provider, with no exceptions.

Client data is never used to train AI models. Reveal's AI Pledge and its LLM providers both guarantee data isn't reused to update any AI technology.

LLM providers can't see, store, or access your data. No queries, responses, or documents are retained outside your client project.

Full transparency into every rating. Each document gets a Yes, Strong Yes, Borderline, or No rating, a plain-language reason, and in-text citations you can jump to directly.

Generative AI in review, without the trade-off on security

Bringing generative AI into document review raises an obvious question: where does sensitive, privileged, and confidential data actually go? Every document sent for AI-Assisted Document Review is packaged with the user's review definition, encrypted, and sent to a designated LLM provider (Amazon Bedrock or Google Vertex AI, depending on region) solely to generate a relevance rating and explanation. Nothing about that exchange is left to chance. Here's what the white paper covers in detail:

The full request lifecycle, from defining review criteria to submitting a job, encrypting documents for transmission, and returning ratings to the document viewer, spans a fully mapped, auditable technical architecture.

LLM providers never store queries, responses, or client data, and have no direct user access or interface into Reveal Enterprise systems; access happens exclusively through Reveal Enterprise APIs.

Reveal's AI Pledge extends to this feature specifically: user definitions, documents, and responses are retained within the client project only, and are never reused to update Reveal's or the LLM provider's AI models.

LLM providers run fully automated abuse monitoring with zero data retention, meaning no human ever manually inspects your queries or documents, even for accounts flagged by automated detection.

Download the White Paper

TLS 1.2/1.3

Encryption standard protecting every query and response exchanged with the LLM provider, in transit

0

Instances of client data used to train Reveal's or the LLM provider's AI models, per Reveal's AI Pledge

100%

LLM providers supported by region (Amazon Bedrock and Google Vertex AI), each governed by the same data protections

Get the full white paper: AI-Assisted Document Review, Security & Data Privacy

A complete technical and policy breakdown of how Reveal AI's AI-Assisted Document Review feature handles your data, for security teams, privacy officers, and legal buyers evaluating generative AI in eDiscovery. This white paper includes:

How the AI-Assisted Document Review architecture works end-to-end, from defining relevancy criteria to secure transmission and rating delivery.

Exactly what data the LLM provider can and can't access, including logging practices, encryption standards, and why AWS and GCP never share logs with the LLM providers themselves.

How Reveal's AI Pledge applies to generative AI features, and what "never used to train AI models" actually means in practice.

How automated abuse monitoring works without human review, including what happens if a potential policy violation is flagged.

Download the White Paper

300M

Lawyering at the Edge of AI: The Emerging Role of Frontier Counsel

Reveal Partners with Thomson Reuters to Connect Evidence Directly to AI Research and Drafting

AI-Assisted Document Review: Security & Data Privacy

Every query and response is encrypted in transit, using TLS 1.2/1.3 between Reveal Enterprise and the LLM provider, with no exceptions.

Client data is never used to train AI models. Reveal's AI Pledge and its LLM providers both guarantee data isn't reused to update any AI technology.

LLM providers can't see, store, or access your data. No queries, responses, or documents are retained outside your client project.

Full transparency into every rating. Each document gets a Yes, Strong Yes, Borderline, or No rating, a plain-language reason, and in-text citations you can jump to directly.

Generative AI in review, without the trade-off on security

The full request lifecycle, from defining review criteria to submitting a job, encrypting documents for transmission, and returning ratings to the document viewer, spans a fully mapped, auditable technical architecture.

LLM providers never store queries, responses, or client data, and have no direct user access or interface into Reveal Enterprise systems; access happens exclusively through Reveal Enterprise APIs.

Reveal's AI Pledge extends to this feature specifically: user definitions, documents, and responses are retained within the client project only, and are never reused to update Reveal's or the LLM provider's AI models.

LLM providers run fully automated abuse monitoring with zero data retention, meaning no human ever manually inspects your queries or documents, even for accounts flagged by automated detection.

TLS 1.2/1.3

0

100%

Get the full white paper: AI-Assisted Document Review, Security & Data Privacy

How the AI-Assisted Document Review architecture works end-to-end, from defining relevancy criteria to secure transmission and rating delivery.

Exactly what data the LLM provider can and can't access, including logging practices, encryption standards, and why AWS and GCP never share logs with the LLM providers themselves.

How Reveal's AI Pledge applies to generative AI features, and what "never used to train AI models" actually means in practice.

How automated abuse monitoring works without human review, including what happens if a potential policy violation is flagged.

Reveal AI

Generative AI, built into the eDiscovery workflow you already trust

AI-Assisted Document Review delivers ratings and reasoning for every document, backed by encrypted transmission and zero data retention

Supports both Amazon Bedrock and Google Vertex AI by region, so security posture stays consistent everywhere Reveal operates

Built on Reveal's AI Pledge: your data is never used to train Reveal's or any third-party AI models

Trusted by thousands of modern legal teams globally
‍

Lawyering at the Edge of AI: The Emerging Role of Frontier Counsel

Reveal Partners with Thomson Reuters to Connect Evidence Directly to AI Research and Drafting

Every query and response is encrypted in transit, using TLS 1.2/1.3 between Reveal Enterprise and the LLM provider, with no exceptions.

Client data is never used to train AI models. Reveal's AI Pledge and its LLM providers both guarantee data isn't reused to update any AI technology.

LLM providers can't see, store, or access your data. No queries, responses, or documents are retained outside your client project.

Full transparency into every rating. Each document gets a Yes, Strong Yes, Borderline, or No rating, a plain-language reason, and in-text citations you can jump to directly.

Generative AI in review, without the trade-off on security

The full request lifecycle, from defining review criteria to submitting a job, encrypting documents for transmission, and returning ratings to the document viewer, spans a fully mapped, auditable technical architecture.

LLM providers never store queries, responses, or client data, and have no direct user access or interface into Reveal Enterprise systems; access happens exclusively through Reveal Enterprise APIs.

Reveal's AI Pledge extends to this feature specifically: user definitions, documents, and responses are retained within the client project only, and are never reused to update Reveal's or the LLM provider's AI models.

LLM providers run fully automated abuse monitoring with zero data retention, meaning no human ever manually inspects your queries or documents, even for accounts flagged by automated detection.

TLS 1.2/1.3

0

100%

Get the full white paper: AI-Assisted Document Review, Security & Data Privacy

How the AI-Assisted Document Review architecture works end-to-end, from defining relevancy criteria to secure transmission and rating delivery.

Exactly what data the LLM provider can and can't access, including logging practices, encryption standards, and why AWS and GCP never share logs with the LLM providers themselves.

How Reveal's AI Pledge applies to generative AI features, and what "never used to train AI models" actually means in practice.

How automated abuse monitoring works without human review, including what happens if a potential policy violation is flagged.

Reveal AI

Generative AI, built into the eDiscovery workflow you already trust

AI-Assisted Document Review delivers ratings and reasoning for every document, backed by encrypted transmission and zero data retention

Supports both Amazon Bedrock and Google Vertex AI by region, so security posture stays consistent everywhere Reveal operates

Built on Reveal's AI Pledge: your data is never used to train Reveal's or any third-party AI models

Trusted by thousands of modern legal teams globally‍

Trusted by thousands of modern legal teams globally
‍