kelly-legal-casebase-ingest

Automated legal case intake ingests raw judgments and arbitral awards, applies PII redaction, and performs anonymization QA before structuring records. It converts raw legal text into categorized data with issue tags, court metadata, and reasoning snippets.

Anonymization QA for legal judgments automatically flags PII leakage and identifies missing anonymization evidence in legal documents. This ensures strict compliance before records enter an internal database, preventing sensitive data exposure.

You can set up a review workflow using a local Hono-based dashboard that renders a human-in-the-loop interface. Reviewers can approve, revise, or block records directly from this desk to ensure high-quality data ingestion.

Yes, Hono is used to render the local UI for legal document processing. The skill relies on the @hono/node-server dependency to provide a local dashboard for human-in-the-loop review of ingested records.

Running legal case ingest workflows requires local file system access for document processing and a Hono-based environment. These prerequisites allow the system to read raw legal text and render the review dashboard.

Legal case ingest requires human-in-the-loop review to validate anonymization QA and taxonomy compliance. Reviewers verify flagged PII leakage, correct missing anonymization evidence, and block records that fail quality assurance checks.