AI Transformation for a FinTech Lending Platform

Engineering capacity was constrained just as product demand doubled, creating bottlenecks across the entire organization.

The existing setup created significant operational risk:

• Mobile apps under-delivering, with app store ratings reflecting customer frustration
• P0 incidents disrupting operations with no clear ownership
• Website performance lagging, limiting organic growth
• No structured path to AI adoption across the org

As demand grew, these constraints directly limited how fast the platform could scale and how reliably it could serve customers.

• Scaled the engineering organization across lending and credit domains
• Rebuilt mobile apps end-to-end across web, iOS, and Android
• Modernized the platform with observability and clear incident ownership
• Embedded AI-driven tooling directly into day-to-day engineering work
• Refactored corporate web infrastructure for Core Web Vitals performance

This allowed the engineering org to scale capacity without a proportional increase in overhead.

• App store ratings improved from 2.2 to 4.7 on iOS and Android
• P0 critical incidents reduced by 90%
• 300% increase in organic traffic following the web overhaul
• Engineering org running at 2x capacity without proportional overhead
• Team scaled from 25 to 50 engineers

Phased delivery across three workstreams - team structure and hiring, platform reliability and observability, and AI tooling integration, embedded alongside engineering leadership across mobile, web, and backend platform layers.

Key implementation components:

• Team structure and hiring to scale engineering capacity across lending and credit domains
• Platform reliability and observability, including clear incident ownership across P0 issues
• AI tooling integration embedded directly into day-to-day engineering workflows
• End-to-end mobile rebuild across web, iOS, and Android
• Corporate web infrastructure refactored for Core Web Vitals performance