$ git log --all --graph --oneline
Project Commit History
Every project is a milestone. Nearly three decades of engineering excellence, documented through the work we ship.
WhatsApp Integration for Microsoft Dynamics CRM
-A multinational retail company with over 2,000 customer service agents was struggling with fragmented communication channels. Their Microsoft Dynamics CRM had no direct integration with WhatsApp — the primary messaging platform used by 85% of their customer base. Agents were manually copying conversations between platforms, leading to delayed responses, lost context, and a 35% customer dissatisfaction rate.
+We architected and built a full-scale WhatsApp Business API integration layer directly into Microsoft Dynamics CRM. The system included automated workflow routing based on customer intent, AI-powered suggested responses using NLP models trained on historical support data, real-time bidirectional syncing of conversations and customer records, and a custom analytics dashboard for supervisors to monitor agent performance and response quality in real time.
>Increased customer response rate by 40% within the first quarter. Reduced average resolution time from 24 hours to under 2 hours. Eliminated manual data entry across platforms, saving 15,000+ agent-hours per month. Customer satisfaction scores improved from 65% to 92%.
AI-Powered IoT System for Swimming Pool Management
-A facilities management company overseeing 500+ commercial swimming pools across the country was spending millions annually on reactive maintenance. Water quality incidents were frequent, regulatory compliance was inconsistent, and the manual testing process required technicians to visit each site multiple times per week — an unsustainable model that led to rising costs and safety violations.
+We designed and deployed a comprehensive IoT platform with custom-built water quality sensors measuring pH, chlorine, turbidity, temperature, and flow rates in real time. The sensor data fed into a cloud-based AI engine that performed predictive maintenance analysis, anomaly detection, and automated chemical dosing recommendations. A centralized dashboard gave operations teams a real-time view of every pool in their network, with automated alerting for compliance thresholds and predictive scheduling for maintenance crews.
>Reduced operational costs by 30% ($2.4M annually). Eliminated 95% of water quality incidents. Achieved 99.8% regulatory compliance across all monitored facilities. Reduced on-site technician visits by 60%, enabling each technician to manage 3x more locations.
Oil & Gas Industry Digital Transformation Platform
-A major midstream pipeline operator managing 3,000+ miles of pipeline infrastructure was relying on legacy SCADA systems with limited data visibility, no predictive capabilities, and siloed monitoring tools. Unplanned downtime was costing $500K+ per incident, corrosion-related failures were increasing, and field teams had no real-time access to operational data — forcing critical decisions based on outdated information.
+We executed a full-scale digital transformation program. Phase 1 involved deploying 10,000+ IoT sensors along pipeline corridors for pressure, flow, temperature, and corrosion monitoring. Phase 2 integrated the existing SCADA infrastructure with a modern cloud analytics platform, creating a unified operational view. Phase 3 delivered AI-powered predictive maintenance models that identified failure patterns weeks before incidents occurred. The entire system was built with industrial-grade security, including air-gapped network segments and HSM-based encryption.
>Reduced unplanned downtime by 72%, saving an estimated $18M annually. Predicted 89% of corrosion-related failures before they reached critical thresholds. Provided real-time operational visibility to 200+ field engineers via mobile dashboards. Achieved full compliance with PHMSA pipeline safety regulations.
AI-Powered Clinical Decision Support Platform
-A regional hospital network with 12 facilities and 3,000+ healthcare professionals was struggling with diagnostic delays, inconsistent treatment protocols, and an overwhelming volume of patient data from wearable devices and EHR systems. Early warning signs for critical conditions like sepsis and cardiac events were being missed due to alert fatigue and manual review processes, contributing to preventable adverse outcomes.
+We built a HIPAA-compliant clinical decision support platform that ingests real-time data from wearable devices, bedside monitors, and EHR systems. Machine learning models were trained on 5 years of anonymized patient records to detect early warning patterns for sepsis, cardiac arrest, and respiratory failure. The platform delivers intelligent alerts to clinical staff through a custom mobile app, integrates with existing EHR workflows, and provides a telemedicine module for remote specialist consultations with AI-assisted preliminary assessments.
>Improved early detection of critical conditions by 64%. Reduced average diagnostic time from 4.2 hours to 45 minutes for targeted conditions. Enabled remote consultations for 30% of specialist cases, reducing patient transfers by 40%. Achieved full HIPAA, HITECH, and SOC 2 compliance with zero security incidents.
Smart City Infrastructure Platform
-A metropolitan city of 2 million residents was facing rapidly growing challenges in traffic congestion, energy waste, and inefficient waste management. The existing infrastructure relied on disconnected legacy systems with no centralized data visibility. Traffic signal timing was static, streetlight energy consumption was unoptimized, and waste collection routes were fixed regardless of actual bin capacity — leading to wasted resources and declining citizen satisfaction.
+We designed and delivered a city-wide IoT platform that unified traffic management, energy optimization, and waste collection into a single intelligent operations center. The traffic module deployed 2,000+ sensors and camera feeds processed with computer vision to enable adaptive signal timing. The energy module connected 50,000+ smart streetlights with demand-responsive dimming. The waste module deployed fill-level sensors across 10,000+ bins with AI-optimized dynamic routing for collection trucks. All modules fed into a centralized command dashboard used by city operations teams 24/7.
>Reduced average commute times by 18% through adaptive traffic management. Cut streetlight energy consumption by 35%, saving $4.2M annually. Optimized waste collection routes, reducing fleet fuel costs by 28% and missed pickups by 90%. The platform became a national reference model for smart city initiatives.
AI Fraud Detection & Prevention System
-A rapidly growing digital banking platform processing 5 million+ transactions daily was experiencing a sharp increase in sophisticated fraud attacks — including account takeover, synthetic identity fraud, and transaction manipulation. Their rule-based detection system was catching only 38% of fraudulent transactions while generating a 12% false positive rate that was blocking legitimate customers and damaging trust.
+We built a multi-layered fraud detection engine combining real-time transaction scoring, behavioral biometrics, and graph-based network analysis. The core ML pipeline processes transactions in under 50ms, scoring each against ensemble models trained on 3 years of transaction history. A graph neural network identifies fraud rings by analyzing relationship patterns across accounts. The system includes an adaptive rule engine that continuously learns from analyst feedback, and a blockchain-anchored audit trail for regulatory compliance.
>Increased fraud detection rate from 38% to 94%. Reduced false positives from 12% to 1.3%, unblocking $28M in legitimate monthly transactions. Identified 3 major fraud rings within the first 60 days of deployment. Achieved full PCI DSS Level 1 and SOA compliance.
Enterprise Supply Chain Optimization Platform
-A national logistics company managing 15,000+ shipments daily across 200+ distribution centers was operating with disconnected warehouse management systems, manual route planning, and no real-time visibility into fleet operations. Delivery delays averaged 22%, fuel costs were escalating, and warehouse utilization was below 60% — all contributing to eroding margins and customer churn.
+We built an end-to-end supply chain platform that unified warehouse management, route optimization, and fleet tracking into a single real-time system. The warehouse module used computer vision for automated inventory tracking and AI-powered demand forecasting for optimal stock placement. The routing engine processed real-time traffic, weather, and delivery window data to generate dynamic routes updated every 15 minutes. Fleet tracking with IoT-enabled vehicles provided live ETAs to both dispatchers and end customers.
>Reduced delivery delays from 22% to 4%. Improved warehouse utilization from 58% to 87%. Cut fleet fuel costs by 19% through AI-optimized routing. Real-time tracking improved customer satisfaction scores by 34%.
High-Performance E-Commerce Platform Migration
-A major online marketplace serving 8 million active users was running on a monolithic ASP.NET application that had been built in 2008. The system experienced critical performance degradation during peak traffic events (Black Friday saw 40-minute outages), deployments required 6-hour maintenance windows, and the tightly coupled architecture made it impossible to scale individual services or adopt modern development practices.
+We executed a phased migration from the legacy ASP.NET monolith to a modern microservices architecture. We decomposed the system into 35+ independently deployable services using a strangler fig pattern to ensure zero downtime during migration. The new architecture was built on Go and Node.js backends with a React storefront, backed by a polyglot persistence layer (PostgreSQL, Redis, Elasticsearch). We implemented event-driven communication via Kafka, a comprehensive CI/CD pipeline, and auto-scaling infrastructure on Kubernetes.
>Achieved 99.99% uptime (zero outages during the next Black Friday). Reduced page load times from 4.2s to 0.8s. Deployment frequency increased from monthly to 50+ deployments per day. Infrastructure costs reduced by 40% through efficient auto-scaling.
Core Banking System Modernization
-A top-50 regional bank with $12B in assets was running core banking operations on a 25-year-old COBOL-based mainframe system. The technology was impossible to integrate with modern digital channels, maintenance costs exceeded $8M annually, regulatory reporting required weeks of manual data extraction, and the institution was losing competitive ground to digital-first challengers offering real-time services.
+We led a comprehensive core banking modernization program using a parallel-run migration strategy. The new platform was built on a microservices architecture with event sourcing for complete transaction auditability. We implemented real-time payment processing, automated regulatory reporting, and open banking APIs compliant with industry standards. The migration was executed without any service interruption to the bank's 1.2 million customers, with a 6-month parallel-run validation period ensuring data integrity.
>Reduced annual maintenance costs from $8M to $2.1M. Enabled real-time payment processing (previously 2-3 business days). Automated 90% of regulatory reporting workflows. Successfully onboarded 3 new digital channel partners within 6 months of launch via open banking APIs.
Autonomous Fleet Management & Telemetry Platform
-An autonomous vehicle company testing a fleet of 200+ self-driving vehicles across 5 cities had no unified platform for fleet telemetry, remote monitoring, or incident analysis. Vehicle data was scattered across multiple systems, safety-critical events took hours to analyze, and the engineering team had no real-time visibility into vehicle decision-making — a critical gap as the company prepared for regulatory approval and commercial deployment.
+We built a comprehensive fleet management and telemetry platform that ingests, processes, and visualizes data from every sensor, camera, and decision module on each vehicle in real time. The system processes 2TB+ of telemetry data daily, with a custom event replay engine that lets engineers reconstruct any moment in a vehicle's journey with full sensor context. We implemented real-time anomaly detection for safety-critical systems, remote vehicle intervention capabilities, and an automated regulatory compliance reporting module.
>Reduced safety incident analysis time from 6 hours to 12 minutes. Provided real-time monitoring of 200+ vehicles across 5 cities from a single operations center. Accelerated regulatory approval timeline by 8 months through automated compliance reporting. Enabled the company to scale from 200 to 500 vehicles without adding operations staff.
$ // More projects in our history — these are the highlights.
$ git stash // 200+ more stored in production