Calculate Cost Savings: Custom Legal Intake Automation

Small law firms often start by stitching together general-purpose automation tools to manage client intake. An email containing a new client's PDF packet might trigger a workflow that sends the file to an OCR service, then to an AI text-summarizer, before finally creating a task in a case management system like Clio or MyCase. This approach works for a few documents a week, but it breaks down under the real-world pressures of a growing practice.

The core issue is economic and architectural. Task-based platforms charge for every single step. One 20-page document can consume 5-10 'tasks' for OCR, classification, and summarization. At 100 new matters per month, a firm can easily burn through 1,000 tasks, pushing them into expensive pricing tiers. These workflows also lack robust error handling or state management. If the AI model misclassifies a document, the workflow fails silently or routes a sensitive real estate closing to a personal injury attorney, requiring manual intervention to fix.

Consider a 10-attorney firm where a paralegal manages intake. A new client emails a signed engagement letter and a 50-page medical record PDF. The multi-step automation extracts the text, but the summary from a generic AI model misses crucial legal context. The paralegal must still read the entire document, manually identify key dates and entities, and copy-paste the correct information into Clio. The automation only created more noise, and the paralegal just spent 25 non-billable minutes on low-value data entry.

The structural problem is that these generic tools cannot be trained on a firm's specific document formats or business logic. They treat a medical record the same as a marketing email. For a process as critical and sensitive as legal intake, a firm needs a system designed for legal documents, with built-in audit trails and human review gates, that doesn't penalize growth with per-task pricing.

The engagement would begin with a thorough audit of your current intake process. Syntora would review samples of every document type for each matter you handle. We map the exact data points that need to be extracted, the business rules for routing, and the required format for your case management system. This discovery phase produces a detailed architecture document you approve before any code is written.

The proposed technical solution is a FastAPI service that runs on your firm's private cloud account. When a PDF arrives via email, the service stores it securely in AWS S3. The system then uses the Claude API, with prompts specifically engineered for legal clause extraction, to classify the matter type, extract key entities, and generate a concise summary. All data processing happens within your controlled environment. A Supabase database provides a complete audit trail for every document.

The delivered system includes a simple human-in-the-loop interface. Instead of a fully automated (and sometimes incorrect) entry, the system creates a draft matter and flags it for paralegal review. The reviewer sees the extracted data and the AI-generated summary side-by-side with the original document, allowing them to verify accuracy in under two minutes before finalizing the entry. You receive the full Python source code, a deployment runbook, and control over the entire system.