Flooded streets in Bengaluru, heat-induced power outages in Delhi, landslides cutting off towns in Himachal—these are no longer anomalies but seasonal expectations. While the frequency and intensity of climate disasters continue to rise, most infrastructure systems across the country are outdated, built for a world that no longer exists.
The cost of this mismatch is huge, in terms of both money and human lives, and it’s mounting each day.
While data can be used to forecast climate-related events and risks, a lot of it is unstructured and fragmented. And the data seldom translates to action.
This is the problem Resilience AI is trying to solve. Founded in 2023, the startup helps urban bodies, governments, and companies figure out which buildings or infrastructure in their cities are most vulnerable to disasters like floods, earthquakes, heatwaves, and landslides, and what to do about it.
“We’re not short on data. We’re short on decisions,” says Samhita R, CEO and Co-founder of Resilience AI. “Our goal isn’t just to show that a city is at risk. It’s to tell people where exactly the risk lies, and how they can fix it before it’s too late.”
A personal history with fragility
Raised in the tea estates of flood-prone Assam, Samhita’s early life was defined by repeated climate disruptions long before they became part of public discourse.
“We had floods almost every year growing up. It wasn’t just water, it was schools shutting down, temporary shelters, and wondering whether normal life would resume the next week,” she recalls. “I don’t come to this work as a technologist first, I come as someone who has lived through the emotional chaos of broken systems.”
After leading large-scale sustainability and infrastructure programmes at Microsoft, GE, and Honeywell, the turning point in her career came in 2021 during Cyclone Yaas. It wasn’t just the disaster that unsettled her, it was also the aftermath that disturbed her.
“It was how eerily familiar it all looked, despite better satellites, forecasts, and budgets. We were failing not because we lacked data, but because we didn’t know how to convert data into action,” she says.
This insight led Samhita to start Resilience AI in 2023, partnering with Sundeep Reddy Mallu, a fifth-generation farmer and climate data scientist, and Dr Anshu Sharma, a disaster-risk expert and the co-founder of SEEDS, a non-profit focused on building resilience in vulnerable communities.
Together, they set out to build a system that transforms early climate warnings into practical, structural interventions.
A system to diagnose and predict vulnerability
Resilience AI’s flagship product, Resilience360, is a software platform that helps users figure out how likely a structure is to suffer damage in the next big flood or earthquake, and how to prevent that. This structure could be a building, a road, a power station, or a school.
For example, a city corporation can use the Resilience software to scan all its schools and hospitals.
The software covers six disaster types—floods, earthquakes, cyclones, heatwaves, wildfires, and landslides—and is trained on data from over 1 million buildings and 29 real disaster events.
Resilience’s software pulls out data from satellites, weather records, sensors, and building maps and shows which buildings are at risk the most, what kind of damage could occur, and what cost it would lead to. Then it suggests what upgrades and safety measures to take—like reinforcing the roof or changing the drainage systems.
“And it does all this quickly. Traditional risk assessments take 8 to 12 months and cost crores. We give you results in 30 minutes. It’s like doing an MRI of a city’s infrastructure,” says Samhita.
Resilience360’s risk predictions are more than 90% accurate and continue to improve with each event, thanks to real-time updates and post-disaster feedback, she adds.
The report that the software generates aligns with global regulatory standards, including that of the Task Force on Climate-related Financial Disclosures, Sendai Framework, and Intergovernmental Panel on Climate Change, to help stakeholders act within compliance boundaries.
Impact so far
Resilience AI works with government agencies, city planners, infrastructure developers, railways, insurers, and large companies. These are organisations that own or oversee hundreds or thousands of buildings, and need to quickly know which ones are at risk and what action to take.
Resilience360 was acknowledged by the National Disaster Management Authority, Ministry of Home Affairs, Government of India, as a disruptive and novel disaster decision support system with applications beyond the public sector.
The software has been adopted in the Delhi Heat Action Plan 2025, Visakhapatnam Flood Action Plan 2025, and Pune and Raigad Flood Action Plan 2024, marking its role in institutionalising disaster technology within administrative systems. It has also been used by Indian Railways and in other projects.
Plug and play
Resilience360 can be plugged into the day-to-day systems that governments and companies already use, like their financial planning tools or maintenance software. It offers real-time risk scores which can influence everything from where a city decides to build a new school to where a company places its next warehouse.
“We didn’t want this to be something managers look at once a month in review meetings,” says Samhita. “It had to be something they live with daily, embedded into their planning, budgets, and operations.”
The system can also be accessed on mobile devices, used in local languages, and linked with smart contracts or insurance calculations.
The startup also has other tools in its repertoire: ResScore, for regulatory and compliance reporting, and ResSuite, which will help insurers and municipalities estimate the financial cost of not acting on risks in time.
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Business model
Resilience AI runs on a subscription-based software-as-a-service (SaaS) model. Clients pay an annual fee depending on the number of buildings they want to assess and the modules they choose—basic diagnostics, forecasting, action planning, or continuous monitoring.
The software provides multi-disaster risk assessment at a starting price of $50 per asset; the cost can go up based on the size and complexity of the organisation.
“We’re not building a consulting firm,” Samhita says. “The software leads. It’s meant to be self-serve for engineers and planners. You shouldn’t need a PhD to use it.”
The startup has a team of 10 people, along with two senior advisors. Their expertise spans software engineering, climate science, policy, and urban planning. Last year, it raised $1 million in funding from Kalaari Capital.
Samhita says the hardest part of running such a software isn’t the technology, it’s the mindset of people. “People don’t budget for what hasn’t gone wrong yet. We’re selling airbags in a world where most people still think seatbelts are enough.”
She points out that the real cost of a flood isn’t just the damaged buildings. It’s the broken supply chains, the lost production time, delayed shipments, rising insurance claims, and mounting financial risks. But the ripple effects aren’t properly factored into most business plans.
To overcome this, the startup is working with insurers to offer discounts to companies that take preventive steps. It’s also embedding its tools into urban planning tenders and ESG (environmental, social, and governance) reporting systems to unlock more money for disaster readiness.
What’s next
Resilience AI is working on a nationwide initiative called Bharat Atlas, which will map the disaster risks of every district, town, and village in India. The goal is to create a live, open data layer that will help governments decide where to invest, where to build, and how to protect people in the face of growing climate threats.
“This isn’t just a tech product. It’s a public utility for resilience. We’re trying to give India the structural intelligence it never had,” says Samhita.
The startup is also expanding internationally, with early interest coming in from cities and agencies in Canada, United States, Australia, and Southeast Asia, which are looking for more proactive, structure-level tools to plan for the consequences of climate change.
(The copy was updated to with additional information.)
Edited by Swetha Kannan
