Automate Payroll Compliance with a Custom AI System

Most small businesses rely on QuickBooks Payroll or Gusto. These platforms are effective for standard W-2 employees in a single state but create hidden risks when complexity increases. Their rigid rule systems cannot adapt to non-standard requirements, forcing finance teams into manual workarounds that introduce errors.

For example, consider a 25-person construction company with projects in two states. QuickBooks cannot automatically apply different prevailing wage rates based on a project code in an employee's timesheet. This forces someone to manually calculate and override pay rates for dozens of line items, risking costly errors. Similarly, a remote-first tech company with an employee who moves from New York to California will find their payroll software handles the state tax change but misses California's specific final pay laws and daily overtime rules.

The structural problem is that off-the-shelf payroll platforms are designed for mass-market simplicity, not regulatory nuance. Their data models are fixed. You cannot create a new rule for something like New York's 'spread of hours' law and have it trigger automatically based on clock-in/clock-out times. The systems are closed, forcing you to manage compliance outside the tool, typically in spreadsheets that are disconnected from the source of truth.

The process starts with a regulatory audit. Syntora maps every state and municipality you operate in, identifying all applicable wage, hour, and tax laws. We then audit your current HRIS and time-tracking systems to understand your data structure. You receive a compliance matrix showing which rules apply to which employees and where your current process has gaps.

The core of the solution would be a Python service running on AWS Lambda that monitors legal APIs or government websites for regulatory changes. The system would use the Claude API to interpret text from new legislation and convert it into structured rules stored in a Supabase PostgreSQL database. For each payroll run, a FastAPI endpoint would ingest timesheet data, apply the relevant rules, and flag discrepancies before the payroll is finalized. This architecture creates a verifiable audit trail for every single calculation.

The delivered system acts as a pre-processing validation layer for your existing payroll platform. Before a payroll run, the engine runs over 200 automated checks against your data in under 5 seconds. It generates a report flagging items like 'Employee #102: 12-hour shift requires California meal break premium.' The system integrates via API, typically costs under $50/month to host on AWS Lambda, and has a 4-week build cycle.