Build Production-Grade AI for Internal Operations

Growing companies often start with visual workflow builders to automate internal tasks like employee onboarding. These tools work for simple, linear sequences like "when new row in Google Sheet, send a Slack message." They begin to break down when a process requires orchestrating multiple systems like an HRIS, a project manager, and a directory service.

Consider onboarding a new software engineer. The process starts when their offer is marked as signed in the HRIS. The system must create a Google Workspace account, a Slack account with specific channel access, a GitHub account with team permissions, and a user profile in the project management tool. A visual builder handles this as a linear chain. But if the GitHub API call fails because the desired username is taken, the entire process halts. Someone has to manually intervene, delete the already-created Google and Slack accounts, and restart the process.

The structural problem is that these visual tools are stateless. Each step is an independent action without the context of the overall transaction. A custom-coded system, by contrast, operates like a state machine. The system knows the employee's onboarding status is "pending_github_creation." If that step fails, it can retry three times with a delay, or it can execute a rollback sequence to undo the previous steps, leaving the system clean and alerting an administrator with a specific error.

This manual failure recovery consumes hours from HR or operations staff each month. It also introduces security risks, as partially-created accounts may be forgotten. Without a persistent, queryable audit log, there is no way to prove compliance or debug why a specific onboarding failed two weeks ago.

The first step is to map your entire internal workflow, from trigger to completion. Syntora would document every system involved (e.g., HRIS, CRM, project manager, directory service) and the specific business rules for each role. This audit produces a state diagram and a sequence diagram that becomes the blueprint for the system, which you approve before any code is written.

The system would be a FastAPI service deployed on AWS Lambda for event-driven execution. When your HRIS fires a "new hire" webhook, the Lambda function triggers. The service uses httpx for asynchronous API calls to the 4 different systems, completing the entire onboarding process in under 10 seconds. We use structlog to create a detailed, machine-readable audit trail for every action, which is stored in a Supabase PostgreSQL database. If an API call fails, the system automatically retries up to 3 times before logging an error and alerting the operations team.

You receive a fully managed system that runs on your own AWS account, costing under $30 per month for typical volumes. You own the complete Python source code, stored in your GitHub repository. The final deliverable includes a runbook detailing how to monitor the system and handle common issues, ensuring you are not locked into a vendor.