Automate Client Onboarding and Document Collection for Your Accounting Firm

Many firms rely on client portals built into practice management software like Karbon or TaxDome. These portals provide a checklist and a secure place to upload files, but they do not process the documents themselves. An accountant still has to open each PDF, find the relevant numbers, and manually type them into the client record or bookkeeping software.

Consider onboarding a new small business client. They upload a prior year's tax return, bank statements from three different banks, and a trial balance from QuickBooks Online. The portal in Canopy confirms the files are received. Your staff then spends 90 minutes opening each file, finding EINs, account numbers, and beginning balances, and re-keying that data into your own system. If a bank statement is missing, the process stops until an associate emails the client and waits for a reply.

The structural issue is that these off-the-shelf portals are designed for secure file exchange, not data extraction and processing. They are generic containers that lack the Optical Character Recognition (OCR) and custom parsing logic needed to understand the structure of a Form 1040 versus a Chase bank statement. They cannot enforce validation rules, like checking if total debits equal total credits in a trial balance before accepting it.

This manual process introduces a 2-3 day lag before real work can begin on a new client. It also creates a high risk of data entry errors that can corrupt bookkeeping from day one. The first impression for a new client is a slow, error-prone process that relies on their accountant performing low-value clerical work.

The first step is a discovery audit of your current onboarding workflow. Syntora maps every document you collect (tax returns, bank statements, payroll reports) and identifies the specific data points needed from each. We then analyze your existing practice management software's API to plan the integration. The output is a clear data flow diagram showing how information will move from a client's PDF to a validated entry in your system.

The core system would be a FastAPI service using Python and the Claude API for intelligent document processing. When a client uploads a document, a Vercel-hosted front end sends it to an AWS Lambda function. This function uses the Claude API to extract structured data based on custom prompts for each document type. Pydantic models then validate the extracted data before writing it to a Supabase PostgreSQL database and syncing it to your main system.

The final system is a secure client-facing portal that provides real-time feedback. If a client uploads a blurry bank statement, the system rejects it instantly with a clear error message. Once all documents are successfully processed, the extracted data populates the new client record automatically. You receive the full source code, a runbook for maintenance, and an admin dashboard to monitor the processing pipeline.