BudgetLenz
A secure, automated personal finance application built to give users clear visibility into spending, auto-categorize transactions, and model goal-based budgeting.
Fintech Pipeline & Secure Account Syncing
Project Overview
Modern users struggle with financial oversight due to multi-card spending and manual categorization limits. BudgetLenz was engineered to address this by securely connecting to user banking systems, pulling transaction feeds, and using machine learning models to automatically bucket spending (e.g., Groceries, Transport, Entertainment) with 99%+ accuracy.
Our studio shipped the native Android & iOS client applications, designed the supporting FastAPI microservices, set up automated vector classification tasks, and established compliance reviews to align with bank security standards.
Key Deliverables
- Secure bank account synchronization using bank-grade OAuth tokens.
- Automated transaction categorization utilizing fine-tuned classification algorithms.
- Intelligent goal-based budget projections with automated alert thresholds.
- Bilingual localized charts, sheets, and monthly spending parameters.
- Offline-first client database sync using local DB structures.
The Challenge
Establishing automated secure banking connection links in compliance with regional regulations while minimizing transaction sync delays. Processing thousands of unstructured transaction strings and placing them into accurate budget buckets in real time was the core algorithmic blocker.
The Solution
Implemented bank-grade OAuth 2.0 flow wrappers coupled with localized parsing queues. Engineered a classification pipeline using a fine-tuned light gradient boosted model that evaluates transaction descriptors, resolving unstructured feeds into precise categories under 150ms.
Measurable Results
Interested in Similar Capabilities?
Discuss fintech architectures, secure system syncs, or custom AI categorization models with our design engineers.