Automate Client Data Collection for Tax Season with AI

Most small firms rely on QuickBooks Online's bank feeds and client portals. QBO's bank rules are a start, but they are brittle. A client's coffee shop purchase described as 'SQ *MERCHANT NAME' one week and 'SQUARE MERCHANT' the next can break a rule, forcing manual recategorization. These tools also fail when a client uploads a PDF bank statement or a 1099-NEC to a portal like SmartVault. The portal is just a secure file box; an accountant still has to download the file, read the numbers, and manually type them into tax software.

Consider a typical client: a consultant operating as an S-Corp. They use Gusto for payroll, Stripe for revenue, and have two bank accounts. For tax prep, you need transaction exports from both banks, payroll summaries from Gusto, and revenue reports from Stripe. You spend an hour just logging into different systems and downloading CSVs. Then you spend another two hours in a spreadsheet manually separating Stripe fees from gross revenue and reconciling transfers between the client's bank accounts.

The structural problem is that off-the-shelf accounting software is built for the business owner, not the firm managing 30 different clients. The software cannot run custom logic, like automatically creating journal entries to split a single Stripe payout into revenue, fees, and liabilities based on your client's business model. Every firm is forced to build its own spreadsheet-based workarounds, creating hours of error-prone work that repeats every tax season.

The first step is a data source audit. Syntora maps every system you need to pull data from for your clients: Plaid for bank accounts, direct API connections for modern payroll like Gusto, and payment processors like Stripe. We identify the highest-value connections that will eliminate the most manual work first. The outcome is a phased build plan, approved by you, before any code is written.

For the technical approach, we would build a central data collection service using Python and FastAPI, deployed on AWS Lambda for efficiency. This service securely stores API credentials and fetches data on a nightly schedule. Transactions and documents are stored in a Supabase PostgreSQL database. This mirrors the architecture Syntora used for its internal accounting system, which successfully automates our own transaction categorization and tax estimates. For PDF documents, we use the Claude API to extract structured data, turning a client's uploaded 1099 into database records without manual entry.

The delivered system is a secure dashboard you own, running in your cloud account. The dashboard provides a single view of all client data, flagging any missing information or transactions that require your review. Instead of hunting for data, you get a clean, categorized dataset ready for your tax software. The system generates standardized exports that import directly, saving hours per client and reducing the risk of data entry errors.