In an era dominated by consumer-facing software, Bhubaneswar-based industrial IoT startup DATOMS is spearheading a global hardware-to-software revolution by connecting legacy industrial machines across continents. Founded by Amiya Samantaray during his student days at NIT Rourkela over a decade ago, the company is capitalizing on a massive surge in industrial automation to bring offline machinery into the cloud era. The venture represents a growing movement to digitize the physical assets that power global supply chains, utilities, and manufacturing plants.
The Invisible Machine Landscape
For decades, heavy industrial equipment like diesel generators, air compressors, and industrial pumps operated in siloed environments. These machines, often referred to as the “invisible backbone” of modern infrastructure, lacked the capability to communicate performance metrics in real time. Operators relied on manual inspections and reactive maintenance, leading to costly unexpected downtime and operational inefficiencies.
The journey to solve this problem began in a modest hostel room at the National Institute of Technology (NIT) Rourkela. Samantaray and his co-founders recognized that while the consumer internet was expanding rapidly, the industrial sector remained largely disconnected. Over the next ten years, the team bootstrapped and refined their technology, transitioning from a campus project into an enterprise-grade Industrial Internet of Things (IIoT) platform.
Bridging the Legacy Gap
The core challenge of industrial digitization lies in the sheer variety of legacy machinery. Factories and utility sites use equipment from different manufacturers, built across different decades, utilizing proprietary communication protocols. DATOMS addresses this fragmentation by providing an OEM-agnostic platform that acts as a universal translator for industrial assets.
By retrofitting older machines with smart sensors and edge computing devices, the platform extracts vital parameters such as fuel consumption, vibration, temperature, and electrical output. This raw data is then transmitted to a centralized cloud platform, transforming dumb machines into intelligent, connected assets. According to industry analysts, this ability to retrofit legacy systems is crucial, as completely replacing industrial machinery is economically unviable for most enterprises.
Data-Driven Efficiency and Market Growth
The economic stakes of industrial downtime are immense. A report by Aberdeen Group estimates that unplanned downtime can cost industrial manufacturers up to $260,000 per hour. By leveraging predictive analytics, DATOMS enables operators to anticipate machine failures before they occur, reducing maintenance costs by up to 30 percent and extending equipment lifespan.
This value proposition aligns with a massive global trend. Market research firm Fortune Business Insights reports that the global Industrial IoT market size was valued at $324.03 billion in 2023 and is projected to grow to over $1 trillion by 2032. This rapid expansion is driven by the urgent need for energy efficiency, carbon footprint tracking, and operational resilience in a post-pandemic global economy.
Scaling Across Continents
What started as a regional effort in India has now expanded into a multi-continental operation. DATOMS has successfully deployed its solutions across Southeast Asia, the Middle East, and Africa, monitoring thousands of assets in real-time. The startup’s software-as-a-service (SaaS) model allows fleet managers and original equipment manufacturers (OEMs) to track their distributed assets from anywhere in the world.
This global footprint highlights a shift in how industrial companies view software. Traditionally, industrial conglomerates built proprietary, closed-loop systems. Today, they are increasingly partnering with agile startups like DATOMS to deploy flexible, cloud-native solutions that can scale rapidly without heavy upfront capital expenditure.
The Autonomous Future
As the industrial sector continues to adopt digital twins and machine learning, the role of real-time data will only grow. Industry experts suggest that the next phase of industrial evolution will move beyond predictive maintenance toward complete machine autonomy. In this future, connected machines will not only report their health but will also autonomously order replacement parts, adjust their operations to optimize energy consumption, and coordinate with other machines on the factory floor.
For industry observers, the trajectory of DATOMS serves as a blueprint for how deep-tech startups from emerging markets can solve global industrial challenges. The focus now shifts to how quickly traditional industries can overcome cultural resistance to digital transformation and embrace the connected machine ecosystem.
