How I built a Zero-Hallucination Data Extraction API using Gemini 2.5 and React

Building AI apps that generate chatty text is easy. Building an AI app that reliably outputs strict database schemas for B2B accounting is hard.

Today, I'm sharing the architecture behind DocuExtract AI: https://ai-factory-viral-wealth-engine-607593765965.us-central1.run.app/

The Challenge

Businesses need unstructured data (invoices, receipts, emails) turned into structured JSON. If the AI hallucinates a number or returns a string like "$1,500.00" instead of a pure integer 1500, it crashes downstream accounting software like QuickBooks.

The Solution

I built a React/Vite app hosted on Google Cloud Run that pipes directly into Google AI Studio.

1. Structured Output: I enforce strict JSON schema mode on the Gemini API.
2. Type Sanitization: The prompt architecture aggressively strips currency symbols and forces pure numeric casting.
3. Failover Routing: If gemini-3.7-flash spikes, the server automatically catches the 503 and fails over to gemini-3.6-flash so the webhook never drops a client file.

You can try the live "Tollbooth" extraction demo here: https://ai-factory-viral-wealth-engine-607593765965.us-central1.run.app/. Let me know what you think of the failover architecture!