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Wheelseye Technology · 2019–2023
// context
Wheelseye is India's largest logistics intelligence platform, connecting truck owners, fleet operators and shippers across the country. Across two roles from 2019 to 2023 I shipped 7 products from scratch and scaled a Next.js architecture from 5,000 to 2M+ active trucks, building real-time shipment tracking over SSE (Server-Sent Events).
// challenge
A rapidly growing logistics platform with multiple products - real-time tracking, FASTag and Razorpay payments, CRM, content, training and B2B/B2C fleet tools - all built on a fragmented legacy codebase with poor performance scores and manual workflows creating operational bottlenecks.
// approach
Shipped 7 products from scratch - from internal ops dashboards to B2B fleet tools and B2C apps - scaling a Next.js architecture from 5,000 to 2M+ active trucks
Migrated the logistics platform to Next.js with SSR optimization - improving Lighthouse scores from 45 to 96 and increasing platform traffic by 40%
Integrated real-time shipment tracking over SSE (Server-Sent Events) with FASTag and Razorpay payments, streaming live location telemetry to 1M+ fleet owners and 500K+ users across 2M+ tracked trucks
Built a Headless CMS with WYSIWYG editing, version control and workflow approvals in React.js, Tailwind and Zustand in under 5 days - cutting content cycle time by 60%
Built a Python and GCP-based web scraper generating 600,000+ leads and scaling daily demand intake from 10 to 300+ while lowering cost per lead
Automated CRM workflows in React.js, TypeScript and Redux - cutting operational headcount from 300 to 120 without degrading output quality or SLA compliance
Replaced all offline training with a Video.js responsive streaming player - enabling 2,500 employees to onboard remotely vs 150 previously
// outcomes
Platform scaled from 5,000 to 2M+ active trucks
Lighthouse 45 → 96
40% increase in platform traffic
7 products shipped from scratch
1M+ fleet owners and 500K+ users streaming live location telemetry
600,000+ leads generated
60% reduction in content cycle time
Support workforce reduced from 300 to 120
2,500 employees onboarded remotely vs 150 previously
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