Many legal teams are already using AI for document review — pasting documents into chatbots and asking them to find differences. The problem isn't that AI can't help. It's that this approach has no consistency, no security architecture, no audit trail, and no structured methodology.
Security risk. Pasting an NDA into a consumer chatbot is a data governance problem. Confidential documents enter a system with no controls over how they are stored, used, or retained.
No consistency. The comparison depends on how the prompt was written that day, by which person, in which session. Two team members get different outputs from the same documents.
No audit trail. A chatbot conversation is not a legal record. Nothing is logged, nothing is timestamped, and nothing is linked to a user or a document version.
Unpredictable cost. Individual AI subscriptions across a legal team add up with no visibility into total spend or volume.
No risk focus. A general AI tool does not know that a jurisdiction change is more material than a formatting change. Sentry does.
Secure by design. Documents processed in a controlled environment. No use for model training. No unmanaged data retention. Built for NDA-level confidentiality requirements.
Consistent every time. The same structured methodology applies to every comparison — regardless of who runs it or when. Your review process is repeatable and team-wide.
Full audit trail. Every comparison logged with a unique ID, timestamp, user attribution, and document reference. Searchable. Exportable. Defensible.
Predictable pricing. Subscription-based per-comparison pricing with clear tiers. No surprise costs. Easy to allocate across teams or client matters.
Risk-aware output. Material clause changes surfaced first. Jurisdiction, term, liability, exclusivity — flagged by significance, not buried in tracked changes.
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