Que: Could you introduce Ubiqedge Technology and share the vision behind building an AIoT Operating System for Infrastructure?

Ans: Ubiqedge Technology is an AIoT infrastructure company focused on making distributed physical infrastructure more intelligent, connected, and operationally efficient. We work across solar, water, air quality, industrial assets, and smart construction — domains where real-time visibility and intelligent control are becoming essential for performance and sustainability.

The idea for building an AIoT Operating System grew directly out of frustration we encountered while working with over a thousand industries, system integrators, and infrastructure operators early on. Every use case required a different form factor, different connectors, and different protocols. And each time a new use case came up, the technology development and deployment cycle stretched from nine to eighteen months — long enough for customers to lose interest entirely. Beyond the timeline problem, there was deep mistrust: companies had invested ten lakh to one crore rupees in digitisation pilots and seen no return — not because the technology failed, but because it was too complex for shop floor teams to operate effectively, and it delivered no automatic benefit without behavioural change.

Our response was not to build a better monitoring tool. It was to rethink the layer entirely. We built both a hardware platform and a software platform — and then focused obsessively on simplification. Today, we can deploy any new use case in one to eight weeks instead of nine to eighteen months. A field technician can complete a physical installation in ten minutes or less. The technology works as a “black box” — hiding backend complexity so completely that customers do not need to understand IoT or AI to extract value from it.

With over 30,000 KLEON units deployed across four verticals — solar, water, air quality, and smart construction — and backed by NVIDIA’s Inception Program, we are building the intelligence layer that India’s infrastructure buildout urgently needs. The long-term vision is to become the AIoT Operating System for industrial infrastructure: a platform that domain experts can configure in natural language — English, Hindi, Gujarati — to build entirely new use cases without depending on us as technology intermediaries. What Apple’s iOS did for consumer applications, we intend to do for industrial infrastructure.

Que: Can you provide an overview of Ubiqedge’s solar monitoring platform and its key features for utility-scale installations?

Ans: Ubiqedge’s solar monitoring platform is designed to provide real-time visibility, analytics, and operational intelligence for solar assets across utility-scale, commercial, industrial, and distributed deployments. The platform integrates field devices, inverters, meters, sensors, weather stations, and energy assets into a centralised monitoring and analytics environment.

For utility-scale installations, key features include real-time generation monitoring, inverter-level and string-level performance tracking, plant-level dashboards, energy generation analytics, weather correlation, fault and alarm monitoring, device health tracking, customised reports, remote diagnostics, and performance benchmarking across sites.

A critical design principle is that SAMASTH is OEM-agnostic. Whether a plant runs Sungrow, ABB, Huawei, or any other inverter make, KLEON connects seamlessly and feeds a unified data model. For asset owners managing mixed portfolios, this means a single pane of glass across their entire fleet — without being held hostage to any inverter vendor’s proprietary platform. The platform also supports BESS integration, making it future-ready for storage-coupled plants that are fast becoming the norm.

What makes our deployment model distinctive is the speed and simplicity with which we go live. Traditional industrial deployments take nine to eighteen months. We deploy a new solar monitoring use case in one to eight weeks. On the ground, a KLEON device is installed in under ten minutes — completely plug-and-play, requiring no field programming. This dramatically lowers the barrier to adoption for EPC contractors, O&M teams, and developers managing distributed portfolios.

Our approach combines edge hardware, secure connectivity, cloud analytics, and AI-driven intelligence so that operators do not just see what is happening at the plant, but understand why it is happening and what action should be taken next.

Que: How does your AI-powered system help improve asset performance ratio, generation efficiency, and asset reliability?

Ans: Solar plants are highly data-intensive assets. Their performance depends on multiple variables including irradiation, module condition, inverter efficiency, temperature, soiling, cable losses, grid availability, and equipment health. An AI-powered system helps by continuously analysing these variables and identifying performance deviations that may not be visible through conventional monitoring.

Most monitoring platforms tell you what happened. SAMASTH tells you what is going wrong before it becomes a loss event.

We approach performance intelligence across three dimensions. First, PR deviation detection — SAMASTH establishes AI-learned baselines for each asset, accounting for seasonal irradiance patterns and temperature coefficients, and flags deviations that static thresholds would miss entirely. Second, generation gap analysis — by continuously benchmarking actual generation against irradiance-corrected expected output, we surface underperforming strings and inverters early, long before they trigger conventional alarms. Third, equipment health scoring — by monitoring device health, alarm patterns, communication behaviour, and operational trends, AI identifies early warning signals before they become major downtime events.

Importantly, our AI is not presented to end users as AI. What matters to a plant operator is not the technology label — it is whether the problem gets solved. Our system surfaces insights in simple, actionable formats: green or red status indicators for shop floor teams, ROI summaries for plant managers, and compiled KPI dashboards for senior management across sites. The intelligence is real; the interface is frictionless.

Over time, this allows developers and O&M teams to move from reactive maintenance to a genuinely predictive operating model — and that shift directly improves performance ratio across the life of an asset.

Que: How does predictive maintenance help solar developers reduce downtime and operational costs?

Ans: Predictive maintenance helps solar developers reduce downtime by identifying potential failures before they lead to generation loss or asset shutdown. In a solar plant, even a small recurring fault across inverters, strings, meters, or communication devices can create significant cumulative energy loss if not detected and resolved quickly.

Traditional maintenance is often either reactive or schedule-based. Reactive maintenance responds after a failure has occurred, while schedule-based maintenance may not reflect actual asset condition. Predictive maintenance bridges this gap by using real-time data, historical trends, alarm patterns, and equipment behaviour to determine where attention is genuinely needed.

This helps O&M teams prioritise field visits, reduce unnecessary inspections, improve spare planning, and address high-impact issues first. It also reduces Mean Time to Detect and Mean Time to Resolve faults, which directly improves plant availability. In practice, this means moving from emergency dispatch to scheduled intervention — which is dramatically cheaper and less disruptive.

From a cost perspective, predictive maintenance improves manpower efficiency, reduces avoidable site visits, prevents escalation of minor faults into major failures, and protects revenue by minimising generation losses. For developers managing large solar portfolios, these operational savings become substantial over time. The platform effectively pays for itself within the first year of deployment.

Que: What differentiates Ubiqedge’s AIoT platform from conventional SCADA and monitoring systems on the market?

Ans: Conventional SCADA and monitoring systems are designed for supervision, control, and data visualisation. They are extremely useful for plant-level monitoring, but remain limited when it comes to advanced analytics, cross-site intelligence, predictive insights, and business-level decision support. Conventional SCADA was built for a different era — centralised, hardware-heavy, and fundamentally reactive. It tells operators what the current state is. It does not learn, predict, or adapt.

The most fundamental differentiator is that Ubiqedge owns the full technology stack: hardware platform, firmware, and software platform — all built in-house. Legacy industrial vendors like Siemens or Honeywell require dedicated programmers to write code against proprietary systems, and customers are locked into their peripheral service ecosystems. We work differently. KLEON and SAMASTH can each be deployed independently or together. There is no lock-in. This gives channel partners and asset owners genuine flexibility — and it signals a different kind of relationship.

Three architectural differences stand out in our platform design. First, SAMASTH is cloud-native and edge-intelligent — KLEON processes data at the source, reducing latency and ensuring continuity even during connectivity disruptions. Second, it is genuinely OEM-agnostic — our data model normalises across inverter makes, BESS vendors, and sensor types, so operators manage a portfolio, not a collection of isolated systems. Third, it is AI-native — rather than manually configured alert thresholds that age poorly, SAMASTH learns what normal looks like for each asset and detects deviation intelligently.

There is also a deployment philosophy difference. Where conventional systems require months of integration, Ubiqedge’s plug-and-play approach means a new installation is live in under ten minutes in the field. This is not an incremental improvement — it is a structural shift in how solar monitoring gets adopted at scale, particularly across distributed rooftop and commercial-industrial portfolios.

In the future, the industry will require systems that are not just monitoring platforms but decision-support systems. That is the direction in which Ubiqedge is building.

Que: Cybersecurity is a growing concern in connected infrastructure. What measures have you implemented to ensure data security and system reliability?

Ans: Cybersecurity is central to connected infrastructure because operational systems are no longer isolated. Solar plants, meters, inverters, gateways, and cloud platforms are all part of a connected ecosystem, and each layer needs to be protected.

The urgency of this in solar specifically cannot be overstated. Historically, the majority of inverter OEMs have been China-based, and solar monitoring data has flowed to overseas servers first before reaching Indian systems. This is a critical infrastructure risk. If energy generation data from solar plants — now a significant and growing fraction of India’s grid supply — sits on foreign servers, it creates real vulnerability: geopolitical disruptions could give external actors the ability to interfere with energy assets. MNRE’s regulatory push for domestic data sovereignty is a direct response to this, and it is one Ubiqedge fully supports by design. All KLEON telemetry is stored and processed on Indian servers.

At Ubiqedge, we follow a security-by-design approach across device, network, cloud, and application layers. At the device level, every KLEON unit uses certificate-based mutual TLS authentication — no device communicates with the cloud without verified identity. Firmware updates are delivered via a signed FOTA pipeline, ensuring no unauthorised code can be pushed to field devices. At the data layer, all telemetry is encrypted in transit and at rest. At the platform layer, SAMASTH enforces role-based access control with granular permissions, full audit trails, and anomaly detection on access patterns.

We also emphasise system reliability through robust device communication, health monitoring, alerts for communication failures, OTA update capability, data validation, and redundancy-oriented architecture. For enterprise and infrastructure customers, reliability is as important as security — because decisions depend on continuous and accurate data availability.

Cybersecurity is not a one-time implementation. It requires continuous monitoring, periodic reviews, controlled user access, auditability, and disciplined operational processes. As AIoT adoption increases in energy infrastructure, we believe cybersecurity and reliability will become core evaluation criteria for every monitoring and automation platform.

Que: As the solar industry becomes increasingly data-driven, what advice would you offer to developers, asset owners, and O&M providers looking to leverage AIoT technologies for long-term operational excellence?

Ans: My advice would be to look at AIoT not as an add-on technology, but as a core operating layer for long-term asset performance. Solar assets have a lifecycle of 20 to 25 years, and the quality of operational intelligence during that lifecycle has a direct impact on generation, reliability, cost, and returns.

First, look for platforms that deliver a “default ROI” from day one — without requiring behavioural change on the shop floor. One of the most consistent reasons AIoT deployments fail in India is not bad technology. It is that the technology depends entirely on people changing how they work. The best implementations build in at least one automated outcome that delivers measurable value immediately — regulatory compliance, automatic anomaly alerting, or energy loss detection — so that trust is established before optimisation efforts begin. We have seen this pattern play out across solar, water, and concrete use cases: once there is a default ROI, customers come back asking for more.

Second, invest in data quality before you invest in algorithms. The silent killer of most AI deployments in the field is poor sensor calibration, inconsistent timestamps, and missing data from connectivity gaps. Without clean and consistent data from inverters, meters, sensors, weather stations, and field devices, advanced analytics cannot deliver meaningful value.

Third, move beyond basic monitoring and invest in platforms that provide actionable intelligence. Dashboards are useful, but the real value comes when the system can identify losses, detect anomalies, predict failures, prioritise maintenance, and support better decision-making. Don’t buy monitoring — buy intelligence.

Fourth, O&M teams must integrate AIoT insights into their daily workflows. Technology delivers value only when insights lead to timely action on the ground — aligning alerts, reports, maintenance planning, field teams, and management reviews with the intelligence the platform generates.

Finally, choose scalable, secure, and OEM-agnostic platforms that can support portfolio growth. Your inverter vendor’s monitoring portal is a walled garden — your data should be yours, portable, and platform-independent. As solar capacity expands, the winners will be those who operate assets with better visibility, lower downtime, stronger reliability, and data-backed decision-making. India’s energy transition will be won or lost in operations — and intelligent infrastructure is how we win it.