#572 — Design a rate recommendation system (vs. potential commission)
Repo: Twill-AI/twill-ai-ui State: open | Status: open Assignee: Ahmad1809
Created: 2025-08-01 · Updated: 2026-03-13
Description
Overview
Design and implement a rate recommendation system that analyzes merchant processing statements and recommends optimal pricing — showing potential savings for the merchant and potential commission for the ISO/agent.
This builds on top of the existing statement analysis pipeline (n8n + PricingStep UI) and connects to the commission estimation logic Ahmad built in facade (#471).
Current State — What Already Exists
1. Fee Inspector (feeinspector.com)
Public-facing statement analysis tool. A merchant or agent uploads a processor statement PDF and gets:
- Current effective rate breakdown (all-in %)
- Fee decomposition (processor markup, PCI, batch, auth, other)
- Card type mix (credit/debit/Amex percentages)
- Partner rate comparisons (Custom Rate, Flat Rate, Interchange Plus)
- Monthly savings estimate vs partner network
The UI shows a “Recommended” partner plan with savings like $24/mo (25% off) and a visual fee comparison bar chart (interchange → assessments → current markup → partner markup → fixed fees).
2. n8n Statement Parsing Workflow
Backend pipeline that powers both Fee Inspector and the in-app PricingStep. Triggered via webhook (POST /webhook/f7b50221-0b54-4d5b-83ca-83bcb51588fb, basic auth).
Flow:
- PDF upload → text extraction → image-based detection (if <50 chars of text per page)
- Image-based path: PDF → JPG (ConvertAPI) → GPT-4o vision → structured extraction (Azure
gpt-4.1) - Text-based path: text preprocessi
Notes
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