Evidence-First AI Document Review for Law Firms
A framework for separating extraction, review, approval, and evidence capture in AI-assisted legal document workflows.
Powerful AI. Controlled legal workflows.
Design and manage AI-assisted workflows while lawyers retain decision rights.
// Lawyer-Controlled Workflow
From document intake to cited first-pass review
Configure document triage, evidence retrieval, review routing, and approval steps around your firm's policies.
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Review & Triage
Structure incoming documents and surface first-pass issues for review by the responsible legal professional.
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Precedent Matching
Retrieve potentially relevant public authorities and link findings to the underlying source for lawyer verification.
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Issue Prioritisation
Use configurable severity, evidence-coverage, and review-status indicators. These are workflow signals, not predictions of legal outcomes.
PUBLIC SOURCE DISCOVERY Pair Search can assist with discovery of public Singapore judgments. Pair is independent of Nesthing; production citations must resolve to the underlying authority.
Explore Pair Search ↗ Nesthing AI Legal Portal Preview
Interface concept
Latest Insights & Articles
View all posts »Technical architecture commentary about governed workflows, evidence handling, and professional oversight.
Model-Agnostic Legal AI: Workflow Control Layer
A practical guide to separating AI models from permissions, approval gates, evidence, and legal workflow integrations.
Human Approval Gates in Legal AI Workflows
A framework for placing human review and approval gates in AI-assisted legal workflows while preserving lawyer decision authority.
Audit Trails for Legal AI Operations
What law firms should reconstruct when an AI workflow reads information, proposes a decision, or attempts an external action.
FAQs
Frequently Asked Questions
What Nesthing proposes, what remains deployment-specific, and where professional review is required.
How does Nesthing approach privacy and data governance?
Privacy roles, model routing, retention, access controls, hosting region, and subprocessors are documented for each agreed deployment. Technical controls can support customer obligations but do not establish legal compliance by themselves.
How can our firm track and allocate AI costs to specific client matters?
Usage and cost records can be designed for internal allocation where the required identifiers, logging, and reconciliation controls have been configured and acceptance-tested.
What is the typical deployment timeline for enterprise teams?
Deployment timing depends on integrations, data classification, security review, source configuration, and acceptance testing.
Can our firm discuss a controlled pilot?
Pilot scope, duration, data limits, responsibilities, acceptance criteria, and exit conditions are agreed before any pilot begins.
How do I request a personalized product demo?
Click "Book a demo" at the top right corner or on the hero button, fill in your company details on our request page, and our team will contact you shortly.