My blog

Category: Case Study

  • Driving Intelligence Across a Leading German Automotive Manufacturer’s Operations with AI-Powered Forecasting

    • Enterprise AI Forecasting Framework – Designed and deployed a centralized, modular AI/ML forecasting architecture to unify forecasting across Finance, Logistics, Procurement, and Sales, replacing fragmented, manual processes with a single source of truth. 
    • Accuracy & Predictive Depth – Achieved up to 80% forecast accuracy across freight costs, transport lead times, and sales, with <20% MAPE for daily and weekly bank balance forecasts—delivering reliable short- and long-term visibility across business functions. 
    • Operational Efficiency at Scale – Automated end-to-end forecasting pipelines, significantly reducing manual effort, minimizing human error, and enabling monthly forecast updates with minimal retraining overhead. 
    • Actionable Business Intelligence – Enabled finance, sales, and logistics teams with real-time, role-specific dashboards to support proactive cash flow management, inventory planning, shipment prioritization, and demand-led decision-making. 
    • Modularity, Scalability & Reuse – Implemented a reusable forecasting framework supporting both univariate and multivariate models, allowing rapid extension to new business use cases, profit centers, and data sources without architectural rework. 
    • Strategic Business Impact – Improved planning precision, strengthened cross-functional alignment, and established a scalable AI foundation to support ongoing digital transformation and enterprise-wide forecasting maturity. 

  • Enabling Data-Driven Demand Planning with AI-Powered Momentum Volume Projection

    • Unified Forecasting Framework – Developed an AI-powered Momentum Volume Projection model to centralize demand forecasting across all product categories and channels.
    • Accuracy & Visibility – Achieved 5–10% forecast error (MAPE) with reliable projections across 1-, 3-, 6-, and 12-month horizons, enhancing business foresight.
    • Operational Agility – Reduced manual forecasting efforts, improved inventory control, and accelerated planning cycles across residential, commercial, and smart access products.
    • Data-Driven Decisioning – Enabled pricing, promotion, and sales teams with real-time dashboards for proactive, evidence-based actions.
    • Scalability & Governance – Deployed a standardized, low-maintenance ML architecture ensuring consistency, model performance, and ease of extension to new product lines.
    • Strategic Outcomes – Strengthened planning precision, improved financial alignment, and established a future-ready AI foundation for sustainable growth.

  • 8X More Flexible Assessments: Modernizing K-12 Evaluation with Scalable Architecture

    • Modern Architecture Upgrade – Rebuilt the client’s flagship Instant Grading platform with a modern foundation, enhancing reliability, uptime, and adaptability to evolving classroom needs.
    • Flexibility & Efficiency – Expanded assessment options from 9 to 75 per question, accelerated development cycles, and simplified onboarding for educators and developers alike.
    • Strategic Outcomes – Delivered 8X more assessment flexibility, ensured smoother scaling to millions of students, and positioned the client as a global leader in next-generation K–12 evaluations

  • Driving Supply Chain Efficiency with Cloud Cost Governance

    FinOps-Driven Visibility & Governance

    Established cross-team accountability with cost allocation, automated tagging, and unified reporting for greater financial and operational transparency.

    Cost Optimization & Automation

    Identified underutilized resources, rightsized workloads, and applied reserved/predictive instances to drive recurring savings.

    Business Impact

    • 20% reduction in annual cloud costs
    • Improved forecasting accuracy and predictability
    • Freed budgets to reinvest in healthcare innovation and supply chain modernization

  • Real-Time Cloud Governance That Safeguards Margins and SLAs

    Cloud Optimization at Scale

    • Predictive Reservation Planning: Used historical usage to recommend Reserved Instances and Savings Plans, maximizing coverage.
    • Dynamic Rightsizing: Built weekly workflows to auto-scale EC2 and RDS instances, matching demand in real time.
    • Governance Automation: Enforced 100% tagging across environments, teams, and apps; eliminated idle EC2, EBS, Elastic IPs, and NAT Gateways.
    • Real-Time Anomaly Detection: Integrated CloudWatch, GCP Monitoring, and Slack alerts to flag deviations before budget breaches.

    Strategic Outcomes

    • Gained real-time cost visibility across AWS, GCP, and third-party tools.
    • Reduced idle resources and eliminated spend blind spots.
    • Improved operational efficiency while safeguarding margins and SLAs.

  • Optimizing Petabyte-Scale Workloads for Cost and Continuity

    Cloud Cost Challenges

    • No centralized tagging, obscuring spend by project.
    • Idle/over-provisioned compute and storage.
    • Finance overshoots of 15–20% with poor forecasting.
    • Reactive anomaly detection post-billing.

    Our Approach

    • Rightsizing & Reservations: Predictive planning and utilization-based tuning.
    • Automated Hygiene: Enforced tagging compliance and removed idle assets.
    • FinOps Governance: Dashboards and KPIs aligned finance, engineering, and ops.
    • Real-Time Monitoring: Anomaly detection with instant alerts.

    Strategic Outcomes

    • 20% cost savings via proactive optimization.
    • 100% tagging compliance for accurate cost attribution.
    • Improved utilization with automation and governance.
    • Sustainable FinOps model supporting future growth

  • Accelerated Bill Inspection MVP with Agentic AI in 2 Weeks

    Agentic Delivery, Continuous Feedback, and Rapid Prototyping

    AI-First MVP Development

    • Built an Agentic AI-powered bill inspection MVP in just two weeks, integrating autonomous sprint execution with Jira automation.
    • Leveraged context-aware Nest.js/Next.js agents for rapid code scaffolding, PR reviews, and AWS Amplify deployments.
    • Spun up interactive UI/UX mockups in hours using v0.dev agents, enabling instant stakeholder feedback and design iteration.

    Closed-Loop Model Refinement

    • Created a seamless feedback loop between AI extraction and human review, instantly feeding corrections back to the model.
    • Automated dataset creation to accelerate LLM improvement cycles and reduce manual intervention.
    • Ensured continuous enhancement of structured data accuracy through iterative validation.

    Strategic Outcomes

    • Delivered a future-ready bill inspection platform with accelerated time-to-market.
    • Reduced dependency on manual review while improving AI accuracy at scale.
    • Enabled full adoption of AI-first development practices across the client’s engineering team.

  • 85% Faster Essay Evaluation: Automating Assessments for a Scalable EdTech Experience

    AI-Powered Essay Evaluation, Consistent Grading, and Scalable Assessments

    AI-Driven Automation

    • Built an AI essay grading system with Generative AI models, integrated Grader and Trainer Dashboards, and a continuous feedback loop for improved accuracy.

    Productivity & Standardization

    • Cut grading time from 45 to under 5 minutes, eliminated bias with standardized rubrics, and ensured consistent scoring across millions of submissions.

    Strategic Outcomes

    • Scaled assessments without extra staff, improved accuracy and turnaround, and strengthened the client’s position as a leader in AI-powered EdTech.

  • Modernizing an eDiscovery Platform for Enhanced Security, Usability, and Efficiency

    Secure Access, Intelligent Workflows, and Scalable Architecture

    Platform Modernization & Authentication Overhaul

    • Abstracted and modularized legacy codebase to enhance maintainability and scalability.
    • Integrated Cerberus FTP for secure, authenticated file transfers critical to legal workflows.
    • Implemented centralized SSO using Auth0 with SAML and OIDC across Microsoft 365, Google Workspace, Okta, and AzureAD.

    Productivity & Experience Transformation

    • Introduced a smart filtering engine with 1,000+ dynamic filters to improve data accessibility.
    • Embedded Pendo-based analytics to monitor user behavior and refine user journeys.
    • Delivered consistent, fast, and secure access for users across platforms.

    Strategic Outcomes

    • Modernized the core platform to meet evolving legal tech demands.
    • Elevated user experience through seamless login and powerful filtering.
    • Enhanced operational agility and security for handling sensitive legal data at scale.

  • AI‑Driven Churn Prediction Significantly Boosts Membership Retention Efforts

    AI-Powered Retention, Real-Time Risk Detection, and Revenue Protection
    AI-Driven Churn Prediction

    • Built a churn prediction model using supervised learning for real-time risk scoring.
    • Combined behavioral, demographic, and macroeconomic data for accuracy.
    • Enabled early identification of high-risk members to trigger timely outreach.

    Customer Engagement & Efficiency

    • Replaced manual churn forecasting with automated, data-driven insights.
    • Focused retention efforts on high-risk users to maximize impact.
    • Streamlined operations with precise, proactive interventions.

    Strategic Outcomes

    • Improved retention and protected recurring revenue.
    • Shifted from reactive to predictive customer engagement.
    • Scaled churn management across the membership base.