Merchant menus arrived in chaos — scanned PDFs, WhatsApp screenshots, mixed-language documents. I designed a structured semi-automated AI workflow that compressed 100-item menu processing to 5 minutes, and built a replicable SOP for the whole team.
NeroPay's merchant customers — mostly Middle Eastern and Turkish restaurants — needed to submit menu data for system import when joining the platform. But these menus arrived in every format imaginable: PDF scans, WhatsApp screenshots, mixed-language Word documents, with inconsistent field names, price formats, and category structures throughout.
The traditional approach was fully manual data entry. As merchant volume increased, that cost would scale linearly. My judgement: this is pattern-based work with fixed logic. AI can intervene.
I use multiple AI tools daily, but each has a different strength. These choices were deliberate, not default.
This pipeline was built by me and currently run by me, but it was designed to be fully handoff-ready — any team member can follow the SOP without re-asking or re-inventing anything.
Ensure you have the latest field template version. Save to local working folder.
Accepted formats: PDF, image screenshots, WhatsApp photos. If multi-page, combine before uploading.
Upload sample CSV and menu image simultaneously. Use the established prompt template requesting output in the sample's field structure.
Key checks: item name recognition, price fields, category accuracy. Any anomalies: fix manually for that item.
Use system import function to load CSV directly. Confirm item count matches expected. Done.
This pipeline reduced the marginal cost of merchant menu onboarding to near zero. As merchant volume grows, the system scales without adding headcount. The entire SOP is designed for full handoff — my role shifted from executor to process designer.
Choosing Claude over other tools was a deliberate decision based on the nature of the problem. This is a "structural conversion" task, not a "text generation" task. Claude is more stable on field-logic alignment and formatted output.
"AI's value isn't replacing thinking — it's replacing repetition. Menu processing has fixed logic. Once you can clearly describe 'what is the standard format,' AI can execute it reliably."
Designing the prompt is essentially writing rules, not just using a tool. That framing — starting from the problem structure rather than from "what can this tool do" — is how I approach AI integration across every workflow.