PayFlow —First Payment Management System Submission for the Xano AI-Powered Backend Challenge

Source: Dev.to

What I Built

PayFlow is a modern, AI‑first payment management system that allows users to:

• Create accounts and authenticate securely
• Manage digital wallets
• Top up balances using real Stripe payments (test mode)
• Send money to other users instantly
• Track transactions with a full audit trail
• Operate in a multi‑account/team environment

The problem PayFlow solves is building a scalable, production‑ready payment backend quickly, while still applying human engineering judgment on security, data modeling, and workflows.

Instead of relying purely on AI output, I used XanoScript to generate an initial backend, then refined and hardened it inside Xano to meet real‑world payment and security expectations.

Demo

Live App:
PayFlow system

Test Credentials

Email: demo@example.com
Password: password123

Stripe test card

4242 4242 4242 4242
Expiry date: Any future date (e.g. 12 / 34)
CVC: Any 3 digits (e.g. 123)
ZIP / Postal code: Any 5 digits (e.g. 10001)

The AI Prompt I Used

Generate a backend system for an AI-enhanced Wallet & Payment Platform using Stripe.

Include the following:

Database Tables:
- Users (Auth-enabled)
- Accounts (team/multi-user support)
- Wallets: user_id, balance, status, created_at
- Transactions: wallet_id, type (credit/debit), amount, status, reference, description, created_at
- Transfers: from_wallet_id, to_wallet_id, amount, status, description, created_at
- Event Logs: user_id, account_id, action, metadata, created_at

API Endpoints:
- User authentication (signup, login, me)
- Create and fetch wallets
- Create Stripe payment flow to top up wallet balance
- Process Stripe payment and record transactions
- Transfer money between wallets
- Fetch transaction history
- Account and team management
- Event logging for auditing actions

Logic Requirements:
- Secure JWT authentication
- Input validation for all monetary values
- Prevent negative balances
- Create pending transactions before confirmation
- Update transaction status on success or failure
- Stripe API integration with environment variables
- Clean, modular backend logic with comments

Output:
- All database schemas
- API endpoints with example logic
- Secure and maintainable structure

How I Refined the AI‑Generated Code

After importing the generated backend into Xano, I manually refined and hardened it to make it production‑ready.

Key Improvements I Made

Database Normalization

• Before (AI‑generated): Loose field typing, no clear status enums, redundant relationships.
• After (Refined): Strongly typed fields (decimal balances, enums for status), clear wallet → transaction → transfer relationships, centralized EVENT_LOG table for auditing.

Secure Payment Flow

• Before: Direct charge logic without full validation.
• After: Stripe tokenization via frontend, backend‑only Stripe secret usage, explicit success/failure handling, wallet credited only after verified payment, transaction references stored for traceability.

Wallet & Transfer Safety

• Before: Basic debit/credit logic.
• After: Balance checks before transfers, atomic wallet updates, sender + receiver transaction records, clear transfer lifecycle (pending → completed).

Event Logging & Audit Trail

• Before: No reliable audit history.
• After: Centralized EVENT_LOG; every critical action (payment, transfer, login) logged, enabling observability and debugging.

Cleanup & Maintainability

• Removed unused AI‑generated agent tables and non‑existent endpoints.
• Consolidated documentation into concise sections.

My Experience with Xano

Xano made it possible to move from idea → production‑grade backend extremely fast.

What stood out most:

• XanoScript AI generation saved hours of boilerplate work.
• Visual workflows made logic easy to reason about.
• Built‑in auth, background jobs, and integrations simplified complex flows.
• Refining AI output inside Xano felt natural and powerful.

Challenges & Learnings

While working with the XanoScript extension inside VS Code, I learned that backend generation is not a live‑sync process. The AI‑generated output serves as a starting blueprint, but API groups and endpoint wiring must be finalized inside the Xano dashboard. I had to manually create API groups and attach refined logic to ensure correct authentication, validation, and Stripe handling.

Additionally, the API base URL changed during iteration due to Xano’s environment‑based deployment and API versioning model. This required updating frontend environment variables during testing, reinforcing the importance of environment management in real production systems.

The process highlighted the distinction between AI‑assisted generation and human‑led system refinement, ultimately resulting in a more secure and maintainable backend.

Tech Stack Summary

Frontend

• Next.js 16 (Turbopack)
• React 19
• Tailwind CSS + shadcn/ui
• Stripe.js & React Stripe Elements
• React Hook Form + Zod
• Deployed on Vercel

Backend

• Xano (Database, Auth, APIs, Logic)
• XanoScript (AI backend generation)
• Stripe API (test mode)
• JWT Authentication
• RESTful architecture

PayFlow demonstrates how AI‑generated backend code can be transformed into a secure, scalable, real‑world payment system through thoughtful refinement using Xano.