Quick Overview
| Category | Description |
|---|---|
| Client | Mortgage Analytics Company |
| Sector | Fintech / Mortgage Tech |
| Location | United States |
| Tech Stack | Next.js, TypeScript, Flask, Python, PostgreSQL, Docker, DigitalOcean |
The Challenge
This fast-growing fintech company needed to modernize its data processing systems and decision-making workflows. Key challenges included:
- Massive real-time data intake from multiple institutions
- Strict compliance with financial regulations and data protection
- Manual workflows that slowed down insights
- Need for real-time analytics for timely decision-making
- Scalable infrastructure to support platform growth
- High security standards to protect sensitive financial data
The Solution
Custom Data Engine: Built a robust API to aggregate and normalize mortgage rate data in real time across multiple sources.
AI-Driven Predictions: Implemented AI models to automate rate forecasting, improve accuracy, and reduce manual analysis.
Secure Cloud Architecture: Deployed a scalable, Docker-based infrastructure on DigitalOcean with encryption and compliance-first design.
Workflow Automation: Streamlined decision-making processes and reduced bottlenecks with smart backend logic and intuitive dashboards.
The Impact
- +40% improvement in decision-making speed
- 100% compliance with industry security standards
- Reduced operational costs through automation
- Platform scales effortlessly as user base and data grow
- More accurate mortgage rate predictions using AI-powered analytics
As a tech lead, finding Rivka was a game-changer. Their developers ship clean, well-documented code and actually understand system architecture, not just ticket completion. Zero technical debt, responsive communication, and they deliver on time. Finally, an outsourcing partner gets it.
Founder
