Case Law and Review Prioritization

Summarizes case decisions and deposition transcripts, identifies key facts by topic or sequence, prioritizes high-value e-discovery documents, and supports privilege review with entity resolution and legal-role classification.

The Problem

“Case Law Summarization and Review Prioritization for Legal Teams”

Organizations face these key challenges:

High document volumes overwhelm reviewer capacity

Keyword search misses context, paraphrases, and aliases

Deposition summaries are slow to produce and hard to verify

Case decisions are lengthy and require structure-aware condensation

Privilege review is hindered by inconsistent names, aliases, and unclear legal roles

Review teams need defensible outputs with citations and human oversight

Impact When Solved

Earlier identification of hot documents and key evidence in e-discoveryFaster deposition and case decision summarization with citation back to source textLower review cost per document through AI-assisted triageImproved privilege review consistency via entity resolution and legal-role classificationBetter reviewer productivity through issue-based queues and explainable rankings

The Shift

Before AI~85% Manual

Human Does

•Review every case manually
•Handle requests one by one
•Make decisions on each item
•Document and track progress

Automation

•Basic routing only

With AI~75% Automated

Human Does

•Review edge cases
•Final approvals
•Strategic oversight

AI Handles

•Automate routine processing
•Classify and route instantly
•Analyze at scale
•Operate 24/7

Real-World Use Cases

Deposition transcript summarization by sequence or topic

Upload a deposition transcript and get a quick summary of what the witness said, either in order or grouped by topic, with links back to the transcript.

long-document summarization with topic segmentationdeployed feature for deposition workflow.

10.0

Legal document summarisation of case decisions

AI shortens long case decisions into concise summaries so lawyers and the public can understand them faster.

document condensation using structure-aware extractionresearch-stage with concrete methods, including structure-aware unsupervised extractive summarisation.

10.0

AI-assisted entity resolution and legal-role classification for privilege review

The system groups different email names and addresses that belong to the same person, then predicts whether that person is acting in a legal role so reviewers can find attorney-client privilege faster.

entity resolution plus role classification with human validationproduction workflow embedded in relativityone air for privilege pipeline with human-in-the-loop validation.

10.0

AI-assisted prioritization of key or hot documents in e-discovery

Instead of only finding relevant files, the system also helps surface the most important documents first based on lawyer-defined criteria like 'hot' or 'important.'

Priority ranking and triage of documents based on user-defined importance criteriaproposed as part of the described air for review workflow, with concrete user steps outlined.

9.5