Smart Factory Solutions

1. Internet Of Things

2. Fleet Management

3. RFID Solutions

4. Predictive Maintenance

5. Digital Twin

35

Year of experience

1200

Collaegues across India

850+

Successfully Project

300+

Valuable trusted Customers

1

Internet Of Things

INDUSTRIAL CONNECTIVITY AND NETWORKING

Leverage robust technologies like 5G, Wi-Fi 6, and LoRaWAN to create seamless communication between machinery and equipment. Our secure networking solutions ensure real-time data exchange for optimal operational synergy.

Deploy advanced sensors to monitor parameters like temperature, humidity, and machine performance. Real-time data collection and centralized analysis empower predictive maintenance and enhance manufacturing processes.

Process data locally at the network edge for faster decision-making. Using AI and machine learning, we uncover actionable insights from manufacturing data to optimize operations and improve efficiency.

Integrate intelligent robotic systems, AGVs, and cobots to automate repetitive tasks, increase productivity, and enhance workplace safety, transforming factories into fully automated ecosystems.

Streamline supply chain operations with real-time inventory tracking, enhanced logistics, and optimized order fulfillment, ensuring efficiency and reducing lead times.

 
 

Fleet Management

REAL-TIME FLEET VISIBILITY

Gain 24/7 access to live location and operational data of your entire fleet, ensuring seamless monitoring and improved decision-making.

Track driver behavior to ensure safety, maintain discipline, and reduce risks. Our system supports monitoring metrics like speed, braking patterns, and idle times.

Predictive maintenance alerts based on sensor data help reduce downtime and extend vehicle life, ensuring fleet efficiency.

Analyze fuel consumption trends to minimize wastage, improve cost-efficiency, and support environmental sustainability goals.

Manage diverse assets—vehicles, trucks, heavy equipment, and cargo ships—through a hardware-agnostic IoT platform for comprehensive logistics control.

 
 
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4

Predictive Maintenance

REAL-TIME CONDITION MONITORING

IoT sensors continuously collect data like vibration, temperature, and pressure to assess asset health.

AI and ML algorithms analyze patterns to forecast equipment failures, providing actionable alerts before disruptions occur.

Efficient maintenance scheduling reduces spare part wastage and extends asset lifespans, boosting operational efficiency.

Detailed data insights enable identification and resolution of underlying issues, improving overall system performance.

From motor monitoring to factory-wide solutions, predictive maintenance reduces defects, enhances uptime, and supports connected manufacturing ecosystems.

 
 

RFID Solutions

INVENTORY TRACKING

Streamline inventory management by eliminating human errors. Perform accurate audits of inbound and outbound goods effortlessly.

Gain real-time insights into product location, quantity, and type. Automated alerts notify low stock levels in stores or warehouses, ensuring timely restocking.

Enhance the customer experience with single-scan item registration for faster checkouts. Transaction data storage simplifies returns and improves management.

Secure products with encrypted RFID tracking, ensuring authenticity and reducing fraud.

Leverage in-depth data to optimize stock levels, predict demand, and improve overall inventory performance.

 
 
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5

Digital Twin

PRODUCT/PROCESS VIRTUALIZATION & CONTROL

Simulate and test processes using a virtual 3D model created with CAD or 3Ds Max for better control and insights.

Gain actionable insights and AI-driven root cause analysis to identify hurdles and improve production capabilities.

Modify parameters or simulate process changes to adapt to custom orders without impacting budgets or schedules.

Leverage historical data to receive recommendations for improving efficiency, reducing time-to-market, and enhancing customer satisfaction.

Widespread adoption across industries, including healthcare, for advanced simulation and process control.