When disasters strike, it’s often not a lack of data that costs lives, but the inability to make sense of it. From rainfall shifts and satellite imagery to human mobility and public health records, today’s climate data is abundant but siloed and difficult to synthesize. Policymakers and researchers struggle to cut through the noise, connect patterns, and surface answers fast enough to guide response.
Climateverse, a project of CrisisReady (a collaboration between Direct Relief and the Harvard Data Science Initiative), takes direct aim at this issue – beginning in South Asia, a region already on the frontlines of climate risk, and expanding to other countries and regions around the world.
Climateverse is an open-source repository of climate data that makes it easy for communities, researchers, and policymakers to get trusted insights by asking questions in natural language, much like they would on ChatGPT. By layering conversational AI on top of curated datasets, Climateverse turns a fragmented data landscape into a tool anyone can query and understand.
To realize this vision, the Climateverse team partnered with AI Findr, a company whose semantic AI technology already powers customer experiences in complex industries like financial services, retail, and healthcare. Now, those same capabilities are being applied to a new domain: climate and disaster response.
With enterprise-grade infrastructure and a track record of running conversational AI at scale, AI Findr provided the technological backbone that turned Climateverse’s vision into a working research assistant.
“AI Findr built the semantic framework that allowed Climateverse to make these datasets accessible far beyond academia. These datasets are finally discoverable in a format that’s useful to response agencies and policy makers. In response to queries, the AI assistant walks users step by step through identifying and accessing relevant databases, determining the scope and limitations of the datasets, and designing potential analyses,” said Satchit Balsari, Climateverse Lead and Associate Professor in Emergency Medicine, Harvard Medical School.
Available now in India, Climateverse includes an extensive collection of curated datasets spanning climate, agriculture, socioeconomics, and health. Users can ask questions like “Which communities are most vulnerable after cyclones?” and get immediate, interactive answers.
Climateverse India is just the beginning. The initiative will grow into a global network of regional portals, each adapted to local data realities but united by common standards of responsible AI and researcher support.
“Climateverse shows what AI can do at its best: transform overwhelming data into clarity that saves lives. We’re proud to contribute our technology and continue supporting this extraordinary mission,” said Flavia Marsano, Product Leader at AI Findr.
With partners across academia, technology, and humanitarian response, Climateverse seeks to make knowledge accessible, decisions faster, and the future safer for all.
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AI Findr
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Press contact: Anne James, annejames@aifindr.ai
For more information on AI Findr, please contact info@aifindr.ai or visit aifindr.ai.
For more information on Climateverse, please contact communications@crisisready.io or visit crisisready.io and climateverse.net.
About CrisisReady’s Climateverse Project
CrisisReady, a collaboration between Direct Relief and the Harvard Data Science Initiative, operates at the intersection of research and operational disaster response. Its mission is to mainstream the use of novel data into disaster preparedness, response, and recovery models to ensure efforts are timely and effective.
About AI Findr
AI Findr, a spinoff by The Agile Monkeys, is an enterprise SaaS platform that enables companies in retail, financial services, healthcare, and tech to deliver conversational search and product discovery across every touchpoint, with proven gains in customer satisfaction and conversion. Behind the scenes, AI Findr provides deep insights into customer behavior while safeguarding privacy and ensuring accuracy.
This release was published on openPR.
