Litigation evidence chronology
Build a source-linked chronology from productions without making legal conclusions.
What this workflow does
Build a source-linked chronology from productions without making legal conclusions. It separates observed facts from inference, surfaces conflicting evidence, and delivers a review-ready finding set instead of an opaque answer.
What you gain
Counsel-reviewed evidence chronology
What the AI agent changes
How this worked before
Traditional automation could collect records, but a person still had to compare sources, resolve conflicts, and write the conclusion.
What the AI agent changes
The agent links events across inconsistent case materials, preserves provenance, and flags contradictions without making legal conclusions.
Agent trigger
A reviewed production set or new evidence batch is available.
Inputs
- Process context: produced documents, metadata, issue tags, and privilege rules
- Approved policies, ownership, and exception rules
Agent flow
- 1
Collect source material from the approved systems and record its timestamp.
- 2
Cross-check conflicting signals and separate facts from inference.
- 3
Prepare a cited chronology and unresolved conflicts with citations, unknowns, and confidence.
- 4
Deliver the approved report and preserve its evidence set.
Human decisions
After step 3
The accountable process owner approves a cited chronology and unresolved conflicts.
Outcome
- Counsel-reviewed evidence chronology
- Evidence, exceptions, and audit trail
Guardrails
- Label inference separately from observed facts.
- Do not close the investigation while required sources are unavailable.
Risks and mitigations
Missing or stale evidence can produce a confident but incomplete finding.
Show source coverage, conflicts, timestamps, and unanswered questions.
Sources and evidence
Sources establish feasibility or impact. Not every metric comes from an identical implementation.