Each case study includes what problem the client had, what we built, the technology stack, and what changed after we shipped. No vague claims just specific outcomes.
A music streaming platform serving the South Asian diaspora had 28,000 active listeners but short session durations (avg. 18 min vs. 35–40 min industry benchmark) and 15.5% premium churn in the first 90 days. We built a behavioural data pipeline capturing skip points, play duration, search-to-play conversion, and playlist completion rates and used collaborative filtering to generate personalised recommendations. Session length increased from 18 to 31 minutes. 90-day churn dropped from 15.5% to 6.8%.
A manufacturing company's 12-year-old on-premise ERP was causing 25–30 hours per week of manual data reconciliation and frequent machine downtime from delayed maintenance alerts. We replaced it with a Java Spring Boot microservices platform integrated with IoT sensors on the factory floor. Procurement cycles reduced by 85%. Manual reporting eliminated. Machine downtime prediction accuracy improved by 40%.
A digital lending company processing 50,000+ loan applications per month was relying on a rules-based credit scoring system with a default rate above industry benchmarks. We built an ML-powered risk assessment platform using gradient boosting on alternative data signals transaction history, behavioural patterns, and bureau data. Default prediction accuracy reached 91%. NPAs reduced by 34% in the first two quarters post-launch.
A logistics company with 150+ daily deliveries had no real-time visibility into driver location, delivery status, or exceptions. Manual check-ins via phone were creating a 2-hour lag in exception resolution. We built a Flutter mobile app for drivers and a React dashboard for operations, with GPS tracking, geofencing alerts, and automated proof-of-delivery. Delivery delays reduced by 45%. Customer complaints down 60%.
A D2C beauty brand was running on a template Shopify store with no personalisation, 3.2% conversion rate, and high cart abandonment. We built a custom React + Node.js platform with AI-powered product recommendations, dynamic pricing, and a personalised homepage based on browsing history. Conversion rate improved from 3.2% to 6.7%. Revenue tripled within 8 months of launch.
Doctors at a multi-specialty clinic were spending 35–40% of their time on documentation writing clinical notes after patient consultations. We built an LLM-powered clinical notes assistant using a fine-tuned model on medical terminology, integrated with their existing EMR system. Note generation time reduced by 70%. Doctor satisfaction scores improved significantly. The product is now licensed to 12 other clinics.
The same engineers who built these products are available as dedicated developers, project teams, or staff augmentation .
Tell us what you're building. We'll tell you how we'd approach it and what outcomes you can realistically expect.