Matter Summary
Create structured summaries of selected matter materials, including parties, facts, dates, issues, and open questions.
Yonnie for legal teams
Private AI for law firms that cannot risk client data.
Yonnie helps law firms explore AI-assisted workflows while keeping confidential matter information inside a controlled local environment.
It is designed for firms that want the productivity benefits of AI without sending privileged or sensitive client material into public cloud AI tools.
Why legal is first
Legal work is document-heavy, time-sensitive, and privacy-critical.
Law firms are an ideal first market for privacy-first AI infrastructure. The workflows are rich in text, the value of time savings is high, and the privacy requirements are strict.
Yonnie is designed to begin with focused legal workflows, validate value in a demanding environment, and then expand to adjacent regulated sectors.
Legal workflows
Designed for practical legal work.
Chronology Builder
Extract key dates and events from approved documents to support case preparation.
Brief Preparation Support
Generate working outlines and first-pass drafts based on selected internal materials.
Precedent Search
Search approved internal precedent banks and knowledge libraries using natural language.
Discovery Review Support
Triage large document sets and identify potentially relevant themes or entities.
Client Communication Drafting
Prepare first-pass letters, emails, and update notes for human review.
Risk positioning
Client confidentiality stays central.
Yonnie is designed around the premise that sensitive matter data should not be uploaded to public AI systems.
The system supports local processing, controlled knowledge access, and human review, making it suitable for firms that need AI capability but cannot compromise confidentiality.
Anchor legal partner
Become an anchor legal pilot partner.
Yonnie is preparing early legal pilot deployments in Melbourne. Anchor partners will help shape the first legal workflow templates and validate the platform in real-world matter environments.