AllWin Auditor: Vibe Coding a Welfare System

AllWin Auditor Schematic 中文
Executive Summary

Using Gemini 3 Pro and Vibe Coding in Google AI Studio, we built an interactive dashboard — the AllWin Auditor — that replaces costly pre-screening with fraud-proof post-audits while preserving user dignity and saving an estimated $16B yearly in administrative waste.


The Problem

The US SNAP program loses roughly $16 billion annually to manual verification and payment errors. Current gatekeeping is slow, costly, and demeaning. As AI reshapes labor markets, a scalable, dignity-first safety net is required.

The Solution

AllWin Auditor implements a Dual-Track welfare system:

  • Track A (Vulnerable): Guaranteed access with quota management.
  • Track B (General Users): Random Free Lunch lottery to remove entry barriers.

We used Gemini 3 Pro as the reasoning engine by uploading invoices, logs, and food photos and prompting the model to detect statistical anomalies and supply-demand contradictions.

How AI Is Used (Gemini 3 Pro)

  • Native Multimodality: Directly ingest invoices, images, and JSON logs for cross-document reasoning without OCR middleware.
  • Anomaly Detection: Statistical comparison across peers (e.g., ingredient inputs vs claimed outputs).
  • Evolutionary Auditing: Post-audit strategy that dispatches humans only for high-confidence anomalies.
  • Macro & Micro Reasoning: Auto-scaling probability logic and micro-fairness adjustments (consecutive win dampening, vetted-user randomized assignments).
  • Long-Context Profiling: 1M+ token analysis of transaction histories to reduce false-need wins.
  • Privacy-First: Periodic data purging and anonymized audit flows; complex cases flagged for human review.

Case Study — The "Ghost Bakery"

A bakery claims 500 meals but only logs ingredient purchases for 50. Defenses:

  1. Random Allocation: Breaks collusion by preventing users from choosing partner restaurants.
  2. AI Comparison: Gemini flags statistical anomalies by comparing inputs vs outputs and peer bakeries.

Impact & Results

Result: a fully functional dashboard that detects trafficking and bot farms in real-time via natural language prompts. The approach shifts government workflow from pre-screening to efficient post-auditing, saving costs and restoring dignity.

Estimated Savings
$16B / year
Real-time Detection
Trafficking & bot farms

Future Scalability

Model extends to transportation subsidies, basic healthcare, and public-space management. Gemini can ingest policy documents and autonomously propose processes for optimization. Government staff transition from gatekeepers to facilitators; restaurants gain stable revenue.

Allwinism — The Goal

Combining the Random Free Lunch protocol with Taxbymywill concepts builds an AI-powered system for distributing basic survival resources and ensuring no one faces hunger.