AI Transformation for a FinTech Lending Platform

Challenge

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.

Solution

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.

Results

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

Implementation

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