Done-For-You AI Automation for Internal Operations

Growing businesses often rely on a mix of SaaS tools for core functions: Gusto for payroll, QuickBooks for accounting, and HubSpot for customer management. While these platforms have APIs, they do not communicate with each other effectively. Off-the-shelf connectors handle basic triggers but fail when a process requires multi-step, conditional logic.

Consider onboarding a new employee. An operations manager manually enters the person's details from a signed PDF offer letter into the HRIS. Then, they re-type the same information into the IT helpdesk to provision hardware and again into the CRM to create a sales account. This 45-minute, error-prone process is repeated for every new hire. A single typo in an email address can delay an employee's first-day access by hours.

The real failure point is handling exceptions. An employee in California requires 3 specific state-level compliance forms, while one in Texas requires only 1. A sales hire needs a specific CRM license tier, while an engineering hire needs access to a different set of tools. Trying to model this branching logic with simple connectors results in dozens of brittle, parallel workflows that are impossible to maintain and often break silently.

The structural problem is that each SaaS tool is designed as a self-contained system. Their APIs are built for simple data transfer, not for orchestrating a business process that spans multiple departments and legal jurisdictions. The connectors you buy inherit these same limitations. They cannot reliably enforce a sequence of operations or manage error recovery when one system is temporarily offline.

The first step is a process audit. Syntora would map your entire workflow, from a signed document to a fully provisioned employee or client. This audit identifies every manual step, every data field, and every system involved. The output from this 2-day discovery phase is a detailed flowchart and data dictionary that serves as the blueprint for the automation.

The technical approach involves building a central orchestration service using Python and FastAPI. This service acts as the single source of truth for the process. For document-driven workflows, the Claude API can parse a PDF contract or offer letter, extracting key fields like name, start date, and compensation with over 99% accuracy. Pydantic models then validate this data before passing it to downstream systems like Gusto or QuickBooks, preventing bad data from entering your core platforms. The entire service runs on AWS Lambda, keeping hosting costs under $50 per month.

The delivered system is a private API that your team can trigger to initiate the workflow. You receive the complete source code in your company's GitHub repository, a runbook detailing its operation, and a monitoring dashboard showing the status of every process. An operations manager can see exactly where a new hire is in the onboarding pipeline in real time. A standard build of this nature takes 2-3 weeks from kickoff to launch.