Automate Client Onboarding Document Workflows

Firms often start with a secure client portal like ShareFile or a practice management suite like Karbon. These tools are great for storage and task tracking but lack intelligent processing. An admin still has to manually open each PDF, check it against a list, and key data into QuickBooks. This manual review is the bottleneck.

Consider onboarding 5 new clients. That is 20-30 documents (engagement letters, W-9s, prior year returns, bank authorizations) arriving as PDFs in an email inbox. An associate spends half a day downloading, renaming, and verifying each file. If a W-9 is missing a signature, the process stalls. A simple data entry error on an EIN can cause IRS rejection notices weeks later. At 5 new clients a month, this consumes over 20 hours of skilled staff time.

These portal and PM tools treat documents as static files. They cannot read the contents. They rely on human review for every piece of information. This creates a linear, error-prone process that does not scale as the firm grows from 50 to 100 clients. The core problem is the lack of content-aware automation.

Syntora's approach would begin with building a processing pipeline for your existing client documents. The system would use AWS Textract to perform OCR on scanned PDFs, capable of handling varying image qualities. The extracted raw text would then be passed to the Claude API with a specific prompt engineered to extract key entities, such as client name, EIN/SSN, addresses, and document type. This method creates structured data from unstructured PDFs.

Syntora would build a FastAPI service to provide an endpoint for document submission. This service would orchestrate the process: sending the file to Textract, receiving the text, calling the Claude API for extraction, and validating the extracted data against defined business rules (e.g., correct EIN format). Results would be stored in a Supabase Postgres database. The system would be designed for efficient processing of documents.

The FastAPI service would be deployed as a serverless function on AWS Lambda, to manage operational costs effectively. The delivered system would use webhooks to post draft client records or journal entries directly to QuickBooks Online. A custom front-end, built with Vercel, would provide your team with a dashboard to review extracted data and manage documents requiring human oversight.

Syntora would configure structured logging with structlog and pipe logs to Datadog. Monitoring would include alerts configured for processing errors or unusual delays. This proactive monitoring ensures system reliability and facilitates prompt issue resolution.