Tyler Graf

Extracts and summarizes key events from medical records into a structured memo for efficient chronological review.

Extracts facts, causation evidence, and itemized damages from medical records and case documents to draft jurisdiction-appropriate demand letters for personal injury, employment, and insurance bad faith matters.

Builds structured expert witness profiles from CVs, transcripts, and published works, extracting credentials, prior opinions, and case history while flagging testimony inconsistencies and cross-examination vulnerabilities.

Extracts key details, generates structured summaries, and identifies obligations from deposition, hearing, and trial transcripts.

Extracts key case and arbitrator details from arbitration documents, stores them in a data table, and generates AI-powered summaries of all past interactions with each arbitrator.

Analyzes insurance defense case documents to generate and update privileged Case Evaluation & Status Reports for insurers, covering liability, damages, and risk assessment.

Generate motion-supporting draft briefs based on case inputs and, optionally, a prior brief used as a structural and stylistic precedent.

Capture, triage, and approve internal app ideas using a standardized intake workflow with lightweight ROI estimates based on timekeeper billable rates.

Generate draft discovery response documents that insert playbook-based objections for each request and leave structured placeholders for case-specific responses.

The Multi-Doc Timeline App converts legal documents into a live, cite-ready chronology—capturing dates, sources, and parties—so teams can search, update, and export polished timelines without manual fact extraction.

Employee Onboarding Suite automates offer-letter drafting, e-signatures, and AI-powered I-9/W-4 completion in a single, seamless approval workflow.