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Trellis Judicial Analytics

4.7

Paid

Users praise the platform for making state court data searchable like Google, though some find the individual document costs high without a pro plan.

Predictive litigation intelligence and judicial behavioral data for data-driven legal strategy.

Paid pricingAPI availableUpdated 2026-03-17

Best fits

Judicial behavioral mappingMotion grant/deny rate calculation

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Trellis Judicial Analytics interface

About Trellis Judicial Analytics

Trellis is a state court research and judicial analytics platform that utilizes advanced Natural Language Processing (NLP) and Machine Learning to structure millions of legal documents into actionable insights. By 2026, the platform has evolved from a simple docket search engine into a sophisticated predictive modeling tool that maps judicial behavior across thousands of jurisdictions. Its technical architecture leverages Large Language Models (LLMs) to extract ruling outcomes from unstructured PDF filings, allowing legal teams to visualize a judge’s grant/deny rates for specific motion types. The system provides a competitive edge by identifying 'judicial tendencies'—statistically significant patterns in how a judge rules on certain legal issues or procedural hurdles. Positioned at the intersection of Big Data and Legal Strategy, Trellis serves as a critical infrastructure layer for Am Law 200 firms and boutique practices alike, offering a searchable database of state court records that were previously siloed or inaccessible. The platform’s 2026 roadmap includes real-time outcome simulation and automated drafting of motion arguments based on a judge’s previous language preferences.

Core Capabilities

Trellis is a state court research and judicial analytics platform that utilizes advanced Natural Language Processing (NLP) and Machine Learning to structure millions of legal documents into actionable insights.

Main Tasks

Use Cases

Motion for Summary Judgment Strategy

Uncertainty regarding a judge's propensity to grant MSJs in complex tort cases.

VIEW EXECUTION STEPS

1.

Navigate to the Judge's Analytics profile on Trellis.

2.

Filter outcomes by 'Motion for Summary Judgment'.

3.

Cross-reference grant rates with the specific case type (e.g., Personal Injury).

4.

Analyze the judge's previous 'Order' documents to identify preferred legal precedents.

5.

Adjust the motion's focus to address the judge's historical pain points.

Venue Selection / Forum Shopping

Determining which county court offers the most favorable odds for a plaintiff.

VIEW EXECUTION STEPS

1.

Use the 'County Comparison' tool.

2.

Input the legal matter type.

3.

Compare average settlement values and grant rates for similar cases across three counties.

4.

Select the venue with the highest statistical probability of success.

Opposing Counsel Intelligence

Preparing for a settlement negotiation with an unfamiliar law firm.

VIEW EXECUTION STEPS

1.

Search the Law Firm in the analytics dashboard.

2.

View their win/loss record before the current judge.

3.

Assess their historical 'Time to Disposition'—do they settle quickly or drag cases out?

4.

Leverage this data to set a realistic settlement floor.

Expert Witness Vetting

Verifying if a judge has previously admitted or excluded a specific expert witness's testimony.

VIEW EXECUTION STEPS

1.

Search the expert witness's name across all trial court dockets.

2.

Locate 'Daubert' or 'Frye' challenge motions associated with them.

3.

Read the judge's final ruling on their admissibility.

4.

Decide whether to retain the expert based on judicial track record.

Case Duration Forecasting

Managing client expectations regarding the length of litigation.

VIEW EXECUTION STEPS

1.

Input the judge and case type into the 'Milestone' tool.

2.

Review the average 'Days to Trial' and 'Days to Disposition'.

3.

Export the timeline graph into a client-facing report.

4.

Update the litigation budget based on expected case duration.

Identifying 'Pro-Plaintiff' Judges

High-level market analysis for litigation funding firms.

VIEW EXECUTION STEPS

1.

Run a macro-report across a state's judiciary.

2.

Rank judges by overall grant rates for plaintiff-side motions.

3.

Identify outliers with significantly higher-than-average awards.

4.

Direct investment toward cases assigned to those specific benches.

Automated Docket Monitoring

Avoiding manual checks of clunky county court websites.

VIEW EXECUTION STEPS

1.

Upload a CSV of 500 active case numbers.

2.

Enable 'Auto-Sync' for document retrieval.

3.

Set up Slack alerts for any new 'Order' or 'Minute Entry'.

4.

Allow the system to automatically categorize the filing type via AI.