Implement Custom AI Automation for Your Legal Practice

Most small law firms rely on the built-in features of their case management software like Clio or PracticePanther. These tools are excellent systems of record, but their automation capabilities are limited to simple, rule-based triggers. For example, they can send a template email when a case status changes, but they cannot read an incoming PDF to determine what the case is about.

Consider a personal injury practice where new client documents arrive as PDFs in a general inbox. A paralegal must open each email, download the attachment, read the document to identify the matter type, create a new entry in Clio, upload the file, and then manually assign it to an attorney based on caseload. This workflow takes 10-15 minutes per document and is a significant source of non-billable time and potential data entry errors. If that paralegal is sick, a bottleneck forms immediately.

The structural problem is that case management systems are designed to manage structured data, not interpret unstructured documents. They provide forms and fields but lack the AI components needed to extract information from text. Firms try to patch this with email rules or manual processes, but these solutions are brittle and do not address the core issue of turning a PDF into actionable data within your primary system.

The first step would be a two-day audit of your current document workflows. Syntora would map how documents arrive, how they are classified, and where they are stored. We'd review your existing case management system to understand its data model and API capabilities. The outcome is a clear scope document defining one high-value workflow to automate first, like client intake from email.

The technical approach would use a FastAPI service running on AWS Lambda to provide a secure endpoint. When an email with a PDF arrives, it is routed to AWS S3 for storage. The FastAPI service then calls the Claude API to perform OCR and extract key information like client name, matter type, and relevant dates. This structured data is used to classify the document and generate a concise summary. We use Supabase as the database to maintain a persistent audit trail of every document processed.

The delivered system would automatically create a new matter in your case management software, upload the original document, and assign it to the correct attorney with the AI-generated summary. A human-in-the-loop interface would allow a paralegal to review classifications with confidence scores below 95%, ensuring total accuracy. The end-to-end processing time per document would be under 60 seconds.