Lead Docket is an intake and lead management system designed for legal practices. It uses AI to summarize and score potential cases (LeadsAI), centralizes lead tracking, links marketing data to outcomes, supports structured intake forms, automates repeated tasks and follow-ups, and includes built-in payment collection—all while integrating into broader case workflows.

Features and functions of Lead Docket include:

LeadsAI
An optional AI-powered add-on that produces automatic summarizations and predictive assessments. It generates concise lead summaries, message sentiment analyses, and timeline-based notes. For motor vehicle accident (MVA) cases, predictive analysis indicates likelihood categories (e.g., “highly likely” to convert).

Lead Tracking
Centralizes capture of all incoming leads and maintains visibility through the conversion pipeline. The system ensures automated follow-ups, tracks stages and statuses, and enables reporting on metrics—from lead volume to conversion rates—with exportable data by field for operational insight.

Marketing Optimization
Connects lead origination data (e.g., ad sources, intake form submissions) to firm outcomes. Users can input marketing spend and see conversion results and revenue by source, enabling ROI-driven decision-making.

Intake Forms
Offers customizable intake scripts to structure lead data collection and qualification. These forms can integrate with web chat or answering-service workflows, and map directly into case systems like Filevine—including custom "collection sections" for multiple related data items.

Workflow Automation
Implements automated task creation and client messaging to ensure no lead is neglected. Automation manages sequences for follow-ups, referral prompts, and internal reminders, reducing manual oversight.

Payments
Enables secure collection of retainers, consultation, or referral fees via online links supporting credit card and ACH transactions. Payment records integrate with lead profiles and can be synced to downstream case management systems.