Case Studies
Real-world projects demonstrating measurable impact across industries.
SaaS
Result
Reduced projected database workload by 80%, improved critical processing workflows by up to 100x , and significantly lowered infrastructure scaling costs. Enabled support for 50,000+ organizations and 1B+ task events, while improving dashboard, risk detection, and escalation processing performance by 90–99%.
SaaS
Campaign Sentinel – SaaS Database Scalability & AI Readiness Transformation
Problem: Campaign Sentinel's multi-tenant SaaS architecture faced significant scalability challenges due to inefficient database queries, N+1 processing patterns, and real-time aggregation workloads, causing increased response times and operational overhead.
As data volume and customer adoption grew, the platform risked performance degradation, infrastructure cost escalation, and limited readiness for enterprise-scale growth and AI-driven analytics.
Solution: A phased Database Optimization and Scalability Strategy was designed and executed: Platform Stabilization, Risk & Escalation Engine Refactoring, CQRS Read Model Architecture, Asynchronous Reporting, Enterprise Data Architecture
Analysis: Conducted end-to-end workflow analysis, Identified scalability constraints across operational processes, Evaluated business impact of performance degradation, Prioritized optimization roadmap based on risk and ROI
Reduced projected database workload by 80%, improved critical processing workflows by up to 100x , and significantly lowered infrastructure scaling costs.
Enabled support for 50,000+ organizations and 1B+ task events, while improving dashboard, risk detection, and escalation processing performance by 90–99%.
View Case Study CQRSEvent-Driven ArchitectureMulti-Tenant SaaS DesignRead Model OptimizationDatabase PartitioningQuery OptimizationScalability Assessment
Healthcare IT
Result
Reduced operational risk by 35% and improved early detection rates by 50%.
Healthcare IT
AI Healthcare Risk Platform
Problem: Hospitals lacked predictive analytics for patient risk detection, leading to delayed interventions.
Solution: Designed AI-driven data pipeline and risk prediction dashboards with real-time alerting.
Analysis: Conducted data audit across 3 hospital systems and facilitated stakeholder workshops with clinical staff.
Reduced operational risk by 35% and improved early detection rates by 50%.
View Case Study PythonSQLPower BIAzure ML
E-commerce
Result
Increased conversion rates by reducing price-related drop-offs. Improved customer retention through personalized deal experiences. Enhanced customer satisfaction and engagement. Reduced cart abandonment and customer churn. Created a unique competitive advantage in the e-commerce market.
E-commerce
Revolutionising E-Commerce Through Real-Time Negotiation
Problem: Traditional e-commerce platforms rely on fixed pricing, leading to cart abandonment, lost sales, and low customer engagement. This approach does not align with the Indian consumer mindset, where bargaining is a natural part of the buying process.
Solution: Developed a negotiation feature that allows customers to propose their own price. The vendor evaluates factors such as product margins, inventory, customer value, and demand to instantly accept, reject, or counter the offer.
Analysis: Research showed that Indian consumers value the experience of negotiating and feel more satisfied when they secure a better deal. Rising competition, price sensitivity, and demand for personalised shopping experiences highlighted the need for a more interactive purchasing model.
Increased conversion rates by reducing price-related drop-offs.
Improved customer retention through personalized deal experiences.
Enhanced customer satisfaction and engagement.
Reduced cart abandonment and customer churn.
Created a unique competitive advantage in the e-commerce market.
View Case Study Design ThinkingCustomer Journey MappingBehavioral EconomicsCustomer Segmentation
Healthcare IT
Result
The project transformed a broad product idea into a structured implementation plan, enabling predictable development, better stakeholder alignment, reduced delivery risks, and faster execution through a well-defined Agile roadmap. Note: This case study showcases my Business Analysis and Agile Product Management approach through a practical case study exercise. It demonstrates my ability to translate business requirements into actionable development plans.
Healthcare IT
Health Monitoring Platform
Problem: A sports technology company wanted to build a health monitoring platform for professional athletes that could track nutrition, hydration, fitness, and body metrics while allowing coaches to monitor player performance. The challenge was converting high-level business requirements into a structured development plan.
Solution: I developed a complete Agile delivery plan that included dependency analysis, product backlog prioritisation, release planning, sprint planning, and detailed use cases. The solution provided the development team with a clear roadmap for execution.
Analysis: I analysed the business requirements, identified technical and functional dependencies, prioritised user stories, estimated effort using story points, and created a sprint-based roadmap aligned with the team's development capacity. The focus was on reducing delivery risks while ensuring an MVP-first approach.
The project transformed a broad product idea into a structured implementation plan, enabling predictable development, better stakeholder alignment, reduced delivery risks, and faster execution through a well-defined Agile roadmap.
Note: This case study showcases my Business Analysis and Agile Product Management approach through a practical case study exercise. It demonstrates my ability to translate business requirements into actionable development plans.
View Case Study Agile ScrumUser story MappingSprint PlanningRelease PlanningStory point EstimationDependancy AnalysisUse case ModelingProduct Backlog Management
SaaS
Result
Increased conversion rate by 60% and freed 20 hours/week per rep.
SaaS
AI Outbound Sales Automation
Problem: Sales teams spent 60% of time on manual lead qualification and outreach.
Solution: Built AI-powered lead scoring model and automated outreach sequences.
Analysis: Mapped sales workflows and identified automation opportunities through time-motion analysis.
Increased conversion rate by 60% and freed 20 hours/week per rep.
View Case Study PythonSQLJiraHubSpot
FinTech
Result
45% faster product decisions and 30% improvement in feature adoption tracking.
FinTech
Product Analytics Dashboard
Problem: Product team lacked centralized metrics, leading to gut-based decisions.
Solution: Created real-time analytics dashboard with custom KPI tracking and automated reporting.
Analysis: Audited existing data sources and conducted KPI workshops with stakeholders.
45% faster product decisions and 30% improvement in feature adoption tracking.
View Case Study SQLTableauPythonJira
Enterprise
Result
Reduced procurement cycle from 14 days to 3 days.
Enterprise
Enterprise Process Automation
Problem: Manual approval workflows caused 2-week delays in procurement.
Solution: Designed automated approval workflow with role-based routing and audit trails.
Analysis: Process mapped end-to-end procurement flow and identified 12 bottlenecks.
Reduced procurement cycle from 14 days to 3 days.
View Case Study ConfluenceJiraPower BILucidchart
SaaS
Result
Reduced churn by 40% within 6 months of implementation.
SaaS
AI Customer Churn Prediction
Problem: Monthly churn rate of 8% with no early warning system.
Solution: Built predictive churn model with proactive retention workflows.
Analysis: Analyzed 2 years of customer behavior data and identified 15 churn indicators.
Reduced churn by 40% within 6 months of implementation.
View Case Study PythonSQLTableauNotion