These case studies are illustrative examples of the type of work we do, not documented client engagements.

Edge Devices

Smart Factory Monitoring System

Manufacturing Industry

Challenge:

A large automotive parts manufacturer needed real-time visibility into their production lines to reduce downtime and improve Overall Equipment Effectiveness (OEE).

Solution:

Deployed 200+ IoT sensors across 15 production lines with edge computing for real-time analytics. Integrated with existing SCADA systems and created a centralized monitoring dashboard.

Results:
  • 35% reduction in unplanned downtime
  • 28% improvement in OEE
  • $2M annual cost savings
ESP32 MQTT Python InfluxDB
Computer Vision

Precision Agriculture Platform

Agriculture Industry

Challenge:

Agricultural cooperative managing 5,000 hectares needed data-driven insights to optimize irrigation and fertilization while reducing water consumption.

Solution:

Deployed LoRaWAN sensor network for soil moisture, weather monitoring, and crop health analysis using drone imagery with computer vision models for disease detection.

Results:
  • 40% reduction in water usage
  • 22% increase in crop yields
  • Early disease detection reduced losses by 15%
LoRaWAN TensorFlow Azure IoT Hub React
Azure Cloud Integration

E-commerce Azure Migration & Scaling

E-commerce

Challenge:

Growing e-commerce platform experiencing performance issues with on-premise infrastructure. Needed to scale for 10x traffic growth during peak seasons.

Solution:

Migrated monolithic application to microservices on Azure Kubernetes Service (AKS). Implemented auto-scaling, Azure CDN, and Azure Functions for order processing.

Results:
  • 99.99% uptime achieved
  • 70% reduction in page load times
  • 45% reduction in infrastructure costs
Azure AKS Azure Functions Docker Azure DevOps
AI Solutions

AI-Powered Predictive Maintenance

Industrial Equipment

Challenge:

Industrial equipment manufacturer faced high warranty costs due to unexpected failures. Reactive maintenance approach led to costly downtime for customers.

Solution:

Deployed ML models analyzing vibration, temperature, and acoustic data from edge devices. Trained ensemble models to predict failures 5-7 days in advance.

Results:
  • 60% reduction in unplanned downtime
  • 50% decrease in maintenance costs
  • 92% prediction accuracy
PyTorch Edge AI Azure ML TimescaleDB
On-Prem Integration

Smart Building Management System

Commercial Real Estate

Challenge:

30-story office building needed integrated automation for HVAC, lighting, and access control to reduce energy costs and improve tenant comfort.

Solution:

Implemented BACnet-based BMS with occupancy sensors, smart thermostats, and automated lighting. Mobile app for facility management and tenant climate control.

Results:
  • 38% reduction in energy consumption
  • $180K annual energy cost savings
  • 95% tenant satisfaction score
BACnet Modbus Node.js Vue.js
Firmware Development

Vehicle Telematics & Fleet Management

Logistics

Challenge:

Logistics company managing 500+ vehicles lacked real-time visibility into fleet operations, leading to inefficient routing and high fuel costs.

Solution:

Custom OBD-II telematics devices with GPS, accelerometer, and CAN bus integration. Cloud platform for route optimization, driver behavior analysis, and predictive maintenance.

Results:
  • 25% reduction in fuel consumption
  • 18% improvement in on-time deliveries
  • 30% reduction in insurance premiums
STM32 4G LTE Azure Angular
AI Solutions

AI-Powered Remote Patient Monitoring

Healthcare

Challenge:

A regional clinic network needed to monitor chronic-condition patients between visits without increasing staff workload, while staying compliant with healthcare data regulations.

Solution:

Built a wearable vitals monitor feeding an HL7/FHIR-compliant cloud platform, with an ML model that flags anomalies for clinician review and a companion mobile app for patients.

Results:
  • 32% fewer avoidable hospital readmissions
  • Clinicians alerted 6+ hours earlier on average
  • 98% patient adoption after 3 months
nRF52 / BLE HL7 FHIR Azure ML React Native
Data Visualization

Smart Grid Energy Optimization Platform

Energy

Challenge:

A regional energy provider needed to balance load across a growing share of solar and wind generation while cutting down on manual grid analysis.

Solution:

Streamed smart-meter and substation telemetry through a cloud data pipeline into real-time dashboards, with automated demand-response triggers during peak load windows.

Results:
  • 19% reduction in peak-load grid strain
  • 27% faster fault detection and response
  • $650K annual savings on peak demand charges
DLMS/COSEM Kafka Azure Power BI
Firmware Development

Insulin Pump Firmware & Safety Validation

Medical Devices

Challenge:

A medtech startup needed IEC 62304-compliant firmware for a wearable insulin pump, with fail-safe dosing logic that could pass regulatory audit on the first submission.

Solution:

Built bare-metal firmware on a dual-core safety MCU with redundant dosing checks, watchdog supervision, and full requirements traceability for FDA submission documentation.

Results:
  • Passed regulatory audit on first submission
  • Zero dosing-logic defects in 12 months of field use
  • 4-month reduction in certification timeline
ARM Cortex-M4 IEC 62304 FreeRTOS C
Edge Devices

Cold-Chain Monitoring for Grocery Distribution

Retail & Logistics

Challenge:

A grocery distributor was losing perishable inventory to undetected temperature excursions across 40 refrigerated trucks and warehouse cold rooms.

Solution:

Deployed battery-powered edge sensors with local anomaly detection and cellular fallback, triggering instant alerts before a shipment left the safe temperature range.

Results:
  • 62% reduction in spoiled inventory
  • Alerts delivered within 90 seconds of excursion
  • $410K annual savings in write-offs
NB-IoT Edge AI AWS IoT Greengrass Rust
Azure Cloud Integration

Multi-Tenant SaaS Platform Re-architecture

B2B SaaS

Challenge:

A B2B SaaS vendor's single-tenant deployments were becoming unmanageable as customer count grew, driving up hosting costs and slowing down feature releases.

Solution:

Re-architected onto a multi-tenant model on Azure with tenant-isolated data via row-level security, Azure AD B2C for identity, and blue-green deployments through Azure DevOps.

Results:
  • 55% reduction in per-tenant hosting cost
  • Release cadence went from monthly to weekly
  • Onboarded 3x more customers with the same team
Azure AD B2C Azure SQL .NET Azure DevOps
On-Prem Integration

Airport Baggage Handling System Integration

Transportation

Challenge:

A regional airport ran baggage sortation on legacy PLCs with no central visibility, making it hard to diagnose jams or predict conveyor failures before they caused delays.

Solution:

Bridged legacy PLCs and barcode scanners into a local integration layer, feeding a live operations dashboard and automated fault alerts for the ground crew, all running on-site.

Results:
  • 44% faster jam detection and clearance
  • Zero missed-bag incidents traced to blind spots
  • Full visibility with no cloud dependency
OPC UA Siemens PLC Node-RED Grafana
Data Visualization

End-to-End Supply Chain Analytics Dashboard

Logistics

Challenge:

A distributor's supply chain data was scattered across five different systems, forcing planners to build manual spreadsheets to understand inventory and shipment status.

Solution:

Built a unified data pipeline consolidating ERP, WMS, and carrier data into a single warehouse, powering interactive dashboards for inventory, lead times, and delay risk.

Results:
  • 90% less time spent on manual reporting
  • 21% reduction in stockouts
  • Delay risks flagged 3 days earlier on average
Azure Data Factory Snowflake Power BI Python
AI Solutions

AI Demand Forecasting for Retail Inventory

Retail

Challenge:

A multi-store retailer relied on manual, rule-based reordering that left popular items out of stock while overstocking slow movers, tying up working capital.

Solution:

Trained store- and SKU-level demand forecasting models on historical sales, seasonality, and promotions data, feeding automated replenishment recommendations to store managers.

Results:
  • 31% reduction in stockouts on top SKUs
  • 18% reduction in excess inventory
  • Forecast accuracy improved from 68% to 89%
Python Azure ML Prophet Power BI
Computer Vision

Automated Visual Quality Inspection Line

Manufacturing

Challenge:

A components manufacturer relied on manual visual inspection, resulting in inconsistent defect detection and bottlenecks on a high-speed production line.

Solution:

Installed line-side cameras with a custom-trained defect detection model running on edge GPUs, automatically rejecting faulty parts and logging defect types for root-cause analysis.

Results:
  • 99.3% defect detection accuracy
  • 3x faster inspection throughput
  • Customer return rate cut by 47%
OpenCV NVIDIA Jetson PyTorch ONNX

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