I used Gemini 2.5 Flash to parse receipts at scale. Here's what I learned about multimodal OCR in production

CartLens, a receipt-parsing startup, deployed Gemini 2.5 Flash for multimodal OCR across thousands of receipts, achieving 95% structured extraction accuracy in single-pass inference versus traditional two-stage vision-then-LLM pipelines. Strict JSON schema prompting outperformed open-ended extraction significantly, while faded thermal paper remains the primary hallucination trigger. A Flash-to-Pro routing strategy based on layout complexity optimizes cost without sacrificing accuracy on edge cases like multi-column or handwritten receipts. Engineers building document intelligence pipelines should prioritize prompt schema rigidity and model routing over defaulting to maximum model capacity.