Digital Twins + AI: How Indian Cities are Solving Urban Challenges Intelligently

India’s urban governance is now moving towards a smarter tech transformation. What began as city mapping and visualisation exercises is now evolving into intelligent, predictive governance systems, powered by high-fidelity digital twins and agentic AI.

Digital twins are virtual replicas of physical assets or systems that use real-time data to reflect the real-world behaviour.

Educational institutions are playing a growing role in advancing digital twin technologies for regional-scale applications. At the Indian Institute of Technology, Delhi, researchers are developing a digital twin of the Ganga river basin that integrates hydrological models with satellite data and real-time sensor networks. This comprehensive system enables basin-wide flood and drought risk assessment, while also supporting long-term water resource planning and ecosystem management.

Talking to AIM, Sajid Malik, Chairman and MD, Genesys International Corporation, which specialises in advanced mapping, survey, and geospatial services, says that the company has upgraded its city-scale digital twin platform (OysterMap/OysterDT) from a static monitoring tool into what it calls a predictive governance engine.

Genesys implemented a high-fidelity 3D urban spatial foundation in Varanasi and organised it into decision-ready layers to enable planning, monitoring, and faster inter-department coordination. The pan-city deployment covered areas within Varanasi Nagar Nigam limits and involved end-to-end project planning, establishing ground control for positional accuracy, and comprehensive data acquisition.

The project combined manned aerial surveys using LiDAR and optical imagery (nadir and oblique, including RGB/NIR) with terrestrial mobile LiDAR and 360-degree street-level panoramic imagery. These datasets were used to produce 2D and 3D base maps at a 1:500 scale, high-precision elevation models, a 3D reality mesh, and a unified spatial database integrating multiple line-department datasets.

“We evolved the digital twin from a ‘view-and-monitor’ dashboard into an action-oriented decision system by adding an agentic AI layer—AI agents interpret real-world signals, generate recommendations, and trigger workflows with human approvals,” Malik explains.

This approach aims to change how cities respond to risk. Instead of reacting after incidents occur, the system now anticipates them.

“Instead of responding after a waterlogging during monsoon, the system predicts risk based on rainfall forecast, drainage capacity, and historical inundation data, and auto-generates a pre-monsoon waterlogging model with a mitigation plan,” he adds.

In this model, the digital twin is no longer a passive mirror of the city, but a governed decision engine that recommends actions before crises unfold.

For the Varanasi digital twin, the company won the SKOCH Award 2025, recognising its contribution to governance in the urban development category.

Open Models, Governed Intelligence

Technologically, Genesys follows a hybrid architecture that blends open-source AI models with domain-specific intelligence and governance frameworks.

“We use a hybrid approach: open-source foundation models for language, vision, and speech—combined with domain-tuned models and rule-based governance,” Malik says.

The company leverages large language models from Meta’s Llama family and comparable open-source models for agent-based reasoning and multilingual assistance. It also employs vision models such as YOLO for object detection and computer vision-based Segment Anything Models for precise asset extraction, enabling robust multimodal intelligence across use cases.

But Malik emphasises that models alone don’t create value. “We use open-source models as building blocks, but the real value comes from grounding them to authoritative city data and wrapping them with governance, audit trails, and human approvals.”

Why Digital Twins Matter for Indian Cities

For India’s congested urban centres, the value of digital twins lies in breaking departmental silos and enabling system-level governance. According to the TomTom Index, six of the top 10 most congested Asian cities are in India.

“Congested Indian cities face ‘stacked’ challenges—traffic, utilities, flooding, air quality, encroachments, and construction churn—often managed in departmental silos,” Malik notes.

A city-scale digital twin creates a shared operational reality for planners and administrators. “In dense Indian cities, the digital twin helps governments shift from firefighting to prevention, by seeing the full system, not isolated problems.”

Genesys is already executing projects across 8–10 Indian cities, including Varanasi, Mumbai, Pune, and Hubballi, using high-resolution aerial imaging, mobile LiDAR systems and proprietary sensor constellations to build 3D city replicas with 5-cm accuracy, often within just six months.

Digital Twins Beyond Urban Infrastructure

Digital twins can be implemented beyond urban governance. Navneet Mishra, Senior VP & Head, Hexagon R&D India, tells AIM that the same foundational concept is being applied to cultural heritage, healthcare, and precision scanning.

Hexagon earlier collaborated with the Telangana government to create an ultra-high-precision digital twin of the Qutub Shahi Tombs in Hyderabad.

“We did a very high-tech job. It’s one of the most accurate scans [of the monuments] that has ever been done. It was dedicated to the government so that in the future, restoration can be done based on precise nanometer calculations,” Mishra remarks.

He also notes that the Notre Dame Church in Paris, which burned in 2019, was restored based on Hexagon technologies.

Digital twins also enable environmental simulations. “You can see how shadows will fall on a future date, how wind will flow, the cooling effect of water bodies—all these things become naturally available once you have a precise digital copy,” he explains.

Intelligent Cities

What’s emerging is a new model of governance—one in which cities transition from static planning and reactive administration to continuously intelligent systems. 

Genesys’ approach brings together high-fidelity 3D geospatial data, agentic AI-driven decision systems, predictive modelling, real-time sensing, and human-in-the-loop oversight to enable more adaptive, data-driven urban governance.

This leads to faster incident response, better coordination across departments, proactive risk reduction, and long-term infrastructure resilience, monsoon preparedness, congestion management, and urban planning.

As Malik summarises, “Agentic AI turns the digital twin from a passive mirror of the city into a governed decision engine that recommends actions—before issues become incidents.”