PaperTrail: Your Private Financial Co-Pilot Powered by Open-Weight AI 💸

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle

## What I Built

PaperTrail — Your Private Financial Co-Pilot 💸

PaperTrail is a privacy-first financial document manager designed for freelancers, solopreneurs, and independent creators.

It uses open-weight multimodal AI to extract information from invoices and receipts, while a deterministic audit engine checks arithmetic discrepancies before records are exported.

Key features include:

• 🧠 AI-Powered **Extraction:** Turn receipts and invoices into structured financial records.
• 🔐 Privacy-First Architecture: Local-first storage and local inference options for sensitive financial data.
• 🛡️ Smart Audit Desk: Detect mismatched totals and flag errors for review with Nib, your AI audit companion.
• 💰 Tax Intelligence: Estimate tax offsets, track potential ITC/VAT, and generate reimbursement statements.
• 📊 CA-Ready Exports: Organize records into CSV ledgers, printable schedules, and local backups.
• 📱 Offline-First Design: Access locally stored records and cached application features offline, where supported.

PaperTrail helps freelancers spend less time on bookkeeping and more time growing their businesses.

## Demo

Live Demo: https://paper-trail-2pk6.vercel.app

Explore the General Ledger, Variance Resolution Desk, Tax Intelligence Engine, AI Benchmark Studio, and offline capabilities.

## Code

GitHub Repository: https://github.com/ziyadparkar01/Paper-Trail

Tech Stack: React 19, TypeScript, Vite, Tailwind CSS, Dexie.js, IndexedDB, Python FastAPI, and SQLite.

## How I Built It

PaperTrail combines open-weight AI with deterministic financial verification.

• AI Models: Meta Llama 3.2 Vision and Qwen2.5-VL for local document-understanding workflows.
• Local Inference: Ollama and FastAPI integration options for running models locally.
• Audit Engine: TypeScript validation rules check extracted totals and flag discrepancies.
• Storage: Dexie.js and IndexedDB support local-first financial record management.
• Offline Support: Progressive Web App techniques help make cached application features accessible without a connection.

The key design decision is separating AI extraction from financial verification: AI interprets documents, while deterministic code checks the arithmetic.

## Why Does Open Innovation Matter?

Financial documents contain sensitive information, including client billing rates, bank details, and tax identifiers.

Open-weight AI makes local inference and greater control over document processing possible without depending entirely on closed cloud AI APIs.

It also enables developers to customize extraction workflows for regional invoice formats, reduce recurring inference costs, and build more transparent financial tools.

The goal: your financial data, your rules, your control.

## My Agent Session

Built using the AI Studio engineering environment, with a focus on:

• Integrating open-weight document-understanding models.
• Designing a deterministic financial audit engine.
• Building a clean, responsive financial dashboard.
• Implementing local-first storage and offline-oriented functionality.