IoT & Edge Computing
Advanced IoT Integration, Real-Time Edge Analytics, and Scalable Digital
Transformation Solutions.
EMPOWERING INDUSTRIES
In an increasingly connected operational landscape, the ability to arvest, process, and act upon data from physical assets is a critical competitive differentiator. At Niyantras, we bridge the gap between Operational Technology (OT) and Information Technology (IT).
We help businesses harness the power of the Internet of Things (IoT) and Edge Computing to predict trends, automate operations, and deliver deeply personalized experiences. Our approach ensures that every sensor deployed and every algorithm implemented drives measurable business impact, from reducing downtime to optimizing energy consumption.
PRIMARY INDUSTRY VERTICALS
CORE CAPABILITIES
Product First
Engineering Mindset
We don’t just write code; we engineer solutions. Our team adopts a product-first approach to build custom IoT ecosystems that are reliable, secure, and tailored to specific business logic.
REAL-TIME
PROCESSING
By leveraging Edge Computing, we process data closer to the source. This minimizes latency, reduces bandwidth costs, and ensures critical decisions are made in real-time, even without internet connectivity.
SCALABLE
ARCHITECTURE
Our solutions are built for scale. Whether integrating with AWS, Azure, or GCP, we design cloud architectures that handle millions of device messages seamlessly while maintaining robust security.
Build With Confidence.
Work With Our Tech Experts.
Work with our tech experts to navigate the complexities of hardware selection, connectivity protocols (MQTT, LoRaWAN, NB-IoT), and data security. We turn fragmented data into a cohesive strategy.
Proven Results. Real Software.
From prototype to production, we deliver software that powers real-world infrastructure.
Jun 15th, 2024
Smart Grid Energy Monitor
PYTHON · AZURE · IOT · HUB · TIME-SERIES · DB
Developed a distributed energy monitoring system for a utility provider. The solution ingests telemetry from 5,000+ smart meters, utilizing edge gateways to aggregate data before transmission, reducing cloud storage costs by 40% and enabling predictive load balancing.
Nov 5th, 2022
Predictive Maintenance for HVAC
AWS · GREENGRASS · MACHINE LEARNING · NODE.JS
Implemented an IoT solution for a facilities management firm. Sensors monitor vibration and temperature on industrial HVAC units. An edge ML model detects anomalies in real-time, alerting maintenance teams before critical failure occurs.