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Projects / Paiperworks — AI-Powered Finance and Document Management

Independent Product

Paiperworks — AI-Powered Finance and Document Management

A mobile-first personal finance and document management application that helps users scan, categorize, organize and report financial records and documents with AI assistance.

My RoleFull-stack product development
PlatformsiOS · Web
StatusAvailable on the App Store
Open WebsiteView on App Store
Paiperworks finance and document management application screens
01Project Overview02The Problem03The Solution04My Role and Contribution05Key Features06Technical Architecture07Technical Challenges08Key Decisions09Outcome10Status
Development ModelIndependent end-to-end development

I built the product planning, mobile application, backend, integrations and production delivery.

01

Project Overview

  • Paiperworks combines personal finance management and document organization in one product.
  • The mobile app supports daily entry, while the web app focuses on bulk operations, reporting and import-export workflows.

02

The Problem

  • Financial records and documents can be scattered across applications, folders and physical sources.
  • Manual entry, categorization and retrieving historical information can take time.

03

The Solution

  • Images and PDFs are analyzed with OCR and AI, then reviewed and edited by the user.
  • Documents and financial records can be connected with accounts, folders and categories.

04

My Role and Contribution

Product and experience

  • Product concept, scope and mobile-web user experience
  • Camera, scanner, gallery and file flows

Full-stack development

  • React Native Expo, Next.js, Node.js and Express.js
  • PostgreSQL, Prisma, Redis, file storage and subscription infrastructure

05

Key Features

  • AI document analysis
  • OCR and scanning
  • Income, expense and bank statement management
  • CSV and XLSX import-export
  • Reporting and subscription management

06

Technical Architecture

  • The mobile and web apps connect to a centralized REST API.
  • Files are stored in a storage layer while relational data and metadata are managed in PostgreSQL.
  • AI results are presented for user confirmation before becoming final records.

07

Technical Challenges

Reliable AI results

An editable preview flow keeps results reliable across varying document structures.

08

Key Decisions

  • AI output does not directly create a final record.
  • Mobile and web experiences are differentiated by their usage goals instead of sharing one interface.

09

Outcome

  • The iOS app, web app, backend, AI analysis and subscription infrastructure run in production.

10

Status

  • Available on the App Store
  • Production backend active
  • Active development continues

11

Technologies

React NativeExpoNext.jsNode.jsExpress.jsPostgreSQLPrismaRedisAWS S3OCRGemini AIRevenueCat
Zeki AydınAntalya, Türkiye
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