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Litigation Timeline Builder Agent

LegalLitigation Support

Automatically extracts dated events, communications, and filings from case documents to construct and continuously update an interactive litigation timeline.

4
Process steps
5
Integrations
3
Data inputs

Building a comprehensive fact timeline is one of the most time-intensive tasks in litigation preparation, requiring attorneys or paralegals to manually read through thousands of emails, contracts, and filings to identify and sequence relevant events

As new documents are produced or discovered, the timeline must be manually re-checked and updated, and inconsistent date formats or conflicting accounts across sources make manual assembly error-prone

This agent scans incoming case documents for dates, named events, and party references, extracts them into a structured chronological record, and flags contradictions between sources for attorney resolution

It keeps the timeline synchronized as new productions arrive, so trial teams always work from a current, sourced, and cross-referenced factual chronology

The agent triggers whenever new documents are added to the case repository, and it uses NLP-based entity and date extraction to identify events, actors, and referenced documents within each file. Extracted events are normalized against a common timeline schema, cross-referenced with existing entries to detect duplicates or conflicting dates, and linked back to their source documents with page and paragraph citations. An LLM generates a plain-language summary of each event, and the timeline is rendered in an interactive, filterable interface that trial teams can query by date range, party, or topic, with automatic email alerts when significant conflicts or new key events are detected.

1

Extract Events from Documents

  • Scan new productions, emails, and filings for date references
  • Identify named parties, actions, and referenced documents
  • Extract event descriptions using LLM summarization
  • Tag events with source document citations
Outcome: Raw event data is extracted and linked to its supporting source material.
2

Normalize and Sequence Events

  • Standardize date formats and resolve relative date references
  • Sequence events chronologically across all sources
  • Deduplicate events described in multiple documents
  • Cluster related sub-events into higher-level milestones
Outcome: A clean, chronologically ordered event record is established.
3

Detect Conflicts and Gaps

  • Compare overlapping accounts of the same event across sources
  • Flag contradictory dates, actors, or descriptions
  • Identify chronological gaps that may need further discovery
  • Route flagged conflicts to attorney for resolution
Outcome: Discrepancies in the factual record are surfaced before they reach trial preparation.
4

Publish and Maintain Timeline

  • Render the interactive, filterable timeline view
  • Update automatically as new documents are produced
  • Notify trial team of new key events or resolved conflicts
  • Export timeline segments for briefs and exhibit preparation
Outcome: The trial team has a continuously current, sourced case chronology ready for use in filings and preparation.
Relativity
pulls newly produced documents for automatic extraction
CaseMap
syncs structured timeline events and fact records
Microsoft Teams
posts alerts when new conflicts or key events are detected
Box
monitors case document repository for new file uploads
TrialDirector
exports timeline segments formatted for courtroom exhibit presentation