Automate Client Intake and Case Updates for Your Law Firm

Most small law firms rely on case management software like Clio or PracticePanther for workflows. These platforms have client portals and can send templated emails, but their automation is based on simple, fixed rules. They cannot read a PDF attachment from a prospective client, understand that it's a medical record for a personal injury case, summarize its contents, and route it to the correct paralegal. That initial triage remains a manual, time-consuming task.

Consider a 10-attorney firm handling personal injury and real estate matters. An email arrives from a new client with three scanned PDFs. An intake paralegal must download each file, open it, identify its type, create a new matter in Clio, write a summary of the key details, and then assign it to the correct attorney. This workflow takes 10-15 minutes of focused work for every single new inquiry and is highly susceptible to data entry errors or delays.

The structural problem is that case management systems are databases with user interfaces, not language processing engines. Their automation is limited to reacting to structured data changes, like 'when a matter's status changes to 'closed', send a survey.' They have no native ability to perform Optical Character Recognition (OCR) on a scanned document or use a Large Language Model like Claude to classify its content. They are architected for organizing information, not interpreting it.

The project would begin with a thorough audit of your firm's current intake process. Syntora would analyze 100-200 anonymized examples of recent client emails and documents to map the exact decision logic your intake team uses. This audit defines the specific matter types, the key data points to extract for each, and the rules for routing cases to the right attorney or paralegal.

A custom system would use a FastAPI service running on AWS Lambda. When an email hits a dedicated inbox, it triggers the service. The system downloads attachments to a private AWS S3 bucket, uses an OCR library to convert any image-based PDFs to text, and then passes that text to the Claude API. A specific prompt, co-developed with your team, instructs Claude to classify the matter, extract entities like names and dates, and generate a concise summary.

The final output would be a clean, summarized brief posted directly into a new matter in your case management software or a dedicated team channel. The responsible attorney receives this summary within 90 seconds of the original email's arrival. Crucially, the system would include human-in-the-loop gates. This allows a paralegal to review and approve the AI's classification and summary before any formal case actions are taken, ensuring complete oversight.