Case Studies

Deep dives into our most impactful projects, showcasing our problem-solving approach, technical expertise, and measurable results.

E-commerce / Retail

How Puja Divine Achieved Rapid Content Updates with Hybrid Flutter + Next.js Architecture

Client: Puja Divine

Duration
4 Months
Team Size
6 Specialists (2 Flutter Developers, 2 Next.js/React Developers, 1 DevOps Engineer, 1 UI/UX Designer)

Puja Divine transformed their mobile app experience by adopting a hybrid Flutter + Next.js SSR architecture. This innovative approach enables instant content updates for marketing promotions and campaigns without app store approvals, reducing release cycles from weeks to minutes and eliminating forced customer updates.

Key Results

  • Reduced content update cycle from 1-2 weeks to instant deployment (minutes instead of days)
  • Eliminated forced app updates for customers - 100% of content changes happen seamlessly in the background
  • Increased marketing campaign launch speed by 95% - promotions can go live the same day they're designed
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Technology / Mobile Services

From Idea to Production: How TapMont Technologies Delivered SeekHelpers' Cloud-Native Mobile App in 3 Months

Client: SeekHelpers

Duration
3 Months
Team Size
8 Specialists (2 Mobile Developers, 2 Backend Engineers, 1 AI/ML Engineer, 1 DevOps Engineer, 1 UI/UX Designer, 1 Project Manager)

In just 3 months, TapMont Technologies transformed SeekHelpers' innovative service-matching concept into a production-ready, cloud-native mobile app for iOS and Android. Leveraging React Native, AWS serverless architecture, and AI-powered matching algorithms, we delivered a scalable solution that handles 15,000+ concurrent users with 99.95% uptime and 92% user satisfaction.

Key Results

  • Delivered production-ready app in exactly 3 months, meeting the aggressive timeline
  • App performance scores: 4.8/5 on iOS and 4.7/5 on Android with average API response time of 180ms
  • 99.95% uptime in first 3 months post-launch, successfully handling 15,000+ concurrent users during peak events
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