Automate Document Review for Your Litigation Firm

Small firms often try off-the-shelf legal tech like Clio or PracticePanther for case management, but their automation is limited to simple templates and reminders. They cannot analyze unstructured PDF content. Some attempt to use generic OCR tools like Adobe Scan, but these just convert images to text. They do not classify documents or extract specific clauses, leaving paralegals to manually copy and paste information.

A 12-person litigation firm receives 50-100 discovery documents daily via email as PDFs. A paralegal opens each email, downloads the PDF, opens it, identifies it as a 'Medical Record' or 'Deposition Transcript', renames the file according to a strict convention, and moves it to a specific folder. This takes 5-7 minutes per document, consuming over 4 hours of their day.

These manual workflows are brittle and error-prone. A single misclassified document can delay a case filing. The core issue is that generic tools cannot understand legal context. They lack the specialized logic to differentiate a motion to compel from a motion to dismiss, or to extract specific indemnification clauses from a 30-page contract.

Syntora approaches legal document automation as an engineering engagement, starting with a discovery phase to understand your firm's unique document types, required extraction points, and workflow for human review. Based on this, we would design and build a custom system.

The core architecture would involve:

An AWS S3 bucket to receive incoming documents. An AWS Lambda function would trigger on each new upload, initiating document processing. We would use Amazon Textract for optical character recognition (OCR) to convert scanned PDFs into searchable text. Both the raw text and original document would be stored in a Supabase table with a unique identifier, ensuring data integrity and traceability.

A FastAPI service would then process the extracted text. This service would send the text to the Claude API, utilizing carefully engineered prompts to classify documents into your firm's specific matter types and extract key entities such as case numbers, party names, and critical dates. For contracts, the system would identify clauses and compare them against your firm's approved library, highlighting deviations for attorney review. We would configure classification and flagging thresholds based on your risk tolerance.

All processing results would be written back to the Supabase database. Documents flagged due to non-standard clauses or classifications below a set confidence threshold would be routed to a human review queue within the system. Once approved, documents could be automatically renamed and filed according to your firm's conventions. An email summary, including a link to the document and extracted key points, could be sent to the assigned attorney.

A critical component of the delivered system would be a comprehensive audit trail, logged within Supabase. This trail would include the prompt used, the raw API response, and the system's confidence score for every decision, supporting transparency and compliance. We prioritize data privacy; the Claude API processes data in-memory and does not retain client data. The entire system would run within your firm's own cloud infrastructure, ensuring privileged documents remain under your control.

Typical build timelines for a system of this complexity range from 6 to 10 weeks, depending on the number of document types and custom logic required. Your firm would need to provide sample documents, define classification categories, and outline current review workflows. Deliverables would include the deployed cloud infrastructure, source code, and documentation. Hosting costs are designed to scale efficiently, with typical operational expenses for a firm processing several thousand documents monthly being nominal.