Minter Ellison Extends Cicero AI Pilot

Minter Ellison extends pilot of Cicero AI

Published Jul 16, 2025

MinterEllison is expanding its trial of Cicero, Automatise's private-cloud AI platform for litigation teams, following strong results from phase one.

Enhanced Chronologies Drive Efficiency

The initial phase automated chronology creation. MinterEllison's feedback shaped issue-focused chronologies that surface critical facts, filter irrelevant details, and provide confidence scoring for AI-generated outputs.

Matter Explorer: Strategic Case Analysis

Phase two debuts Matter Explorer, which transforms pleadings into structured intelligence. The feature:

  • Maps cases into core elements: facts, claims, issues, causation, witnesses, and evidence

  • Links each element directly to source documents

  • Enables rapid identification of gaps and inconsistencies

  • Creates a foundation for targeted chronologies and investigations

Selected dispute teams will evaluate the tool's speed, accuracy, and usability over three months.

"Automatise impressed us by turning lawyer feedback into practical features within weeks," said Ken Porter, Director of AI and Client Solutions at MinterEllison. "We're excited to see how Matter Explorer enhances our client service."

"MinterEllison's insights have already strengthened Cicero for all users," added Joseph Rayment, Automatise CEO. "Matter Explorer represents our next step in delivering measurable efficiency gains."

The extended pilot begins immediately, with results informing potential for wider deployment.

Book a Working Session.

See how Cicero analyses a real matter end to end.

We work with your documents or a representative dataset to demonstrate the platform in practice.

Book a Working Session.

See how Cicero analyses a real matter end to end.

We work with your documents or a representative dataset to demonstrate the platform in practice.

Book a Working Session.

See how Cicero analyses a real matter end to end.

We work with your documents or a representative dataset to demonstrate the platform in practice.