Spearheading the vision, strategy, design, product buildout and successful launch of 10+ platforms including B2B, B2C and Progressive Web App (PWA) platforms for Jio Health, JioOnePay and JioIoT, revamping the Jio Ecosystem into a modern, AI/ML-enabled digital ecosystem leveraging scalable cloud architecture, generating $30M+ in revenue. Building and scaling IoT-enabled digital platforms with AI-driven appliance-level disaggregation, data insights and personalisation for 30mn+ consumers, resulting in $10 M within 6 months of launch. Using Unsupervised + supervised hybrid models for appliance signature detection, including clustering + pattern recognition for load disaggregation generated personalised insights and tips for the customers resulting in saving of ~ 12% in bills. Led end-to-end implementation of multiple B2B and B2C SaaS Healthcare platforms by driving product roadmaps, trade-offs, and cross-functional alignment using customer insights and data-backed decision making resulting in onboarding 50+ enterprise clients, 100+ providers & 3M+ users generating $6M+ in first 12 months. Conceptualized and launched JioOnePay, an enterprise-grade payment platform integrated with 10+ partners, streamlining payments flows across client systems, driving ~114M monthly transactions, processing $700M in monthly payment volume, and generating $1M in recurring monthly revenue. Architected AI-based product roadmap for Jio Health, launching features like supervised ML models for predictive risk scoring, combined with rule-based Early Warning Score (EWS) algorithms and OCR models enhancing diagnostic accuracy, enabling faster and efficient health interventions and recommendation model. Led development of an AI-powered Doctor Assistant leveraging RAG-based LLMs to interpret structured health reports and past records, generate personalized health insights, resolve user queries, share health tips and compute health scores. Boosted CSAT from 57 to 83 and improved feature stickiness from 4.47% to 13.85% by launching 7 high-impact features and systematically enhancing UX, engagement loops, and platform performance. Deployed AI-powered chatbot and WhatsApp automation along with CRM for customer 360 degree profiling, reducing support ticket volume by 32% and drop-off rate across journeys by 27%, improving TAT for resolution by 37%, significantly enhancing operational efficiency. Developed an AI-driven customer segmentation engine using clustering, enabling personalized journeys and driving an 18% activation uplift, 12% retention improvement, and 32% increase in campaign ROI. Partnered with data scientists and ML engineers to refine data, tune models, and deploy iterative enhancements to improve segmentation accuracy and business impact.