RELIEF-AI

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  Home Page

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  Dashboard

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  User interface for Reporting

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  User Feedback

Inspiration

During natural disasters, the biggest challenge is that victims cannot communicate their needs quickly. Many people cannot type, phone networks get overloaded, and language differences slow down rescue operations. We were inspired to build a system that allows anyone—even in panic or without literacy—to report their needs using just their voice. This motivated us to create RELIEF-AI, a voice-first, multilingual reporting system for disaster response.

What it does

RELIEF-AI lets disaster victims send a simple voice message in their local language, and automatically converts it into clear, structured, and visual information for relief teams. It uses Whisper for transcription, GPT for data extraction, and icons for instant understanding. A live map dashboard shows where help is needed most, making rescue operations faster, smarter, and more organized.

How we built it

We built RELIEF-AI using Base44’s no-code workflows combined with AI APIs. Voice recordings are captured through a web/IVR interface and processed using Whisper for speech-to-text. The text is then analyzed by GPT, which extracts key fields like number of people, injuries, needs, and urgency. A visual icon is generated for quick viewing, and all reports are displayed in real time on a map-based dashboard integrated with Google Maps.

Challenges we ran into

We faced challenges in handling noisy audio, extracting accurate data from unstructured speech, and resolving unclear location information. Another challenge was ensuring the system works smoothly across multiple Indian languages and remains usable even in low-network conditions. Designing a workflow that stays simple while using multiple AI tools together was also a big challenge.

Accomplishments that we're proud of

We are proud that RELIEF-AI successfully transforms ordinary voice messages into structured, prioritized, and visual disaster reports within seconds. We built a working pipeline using only no-code tools, integrated multi-language support, and created a dashboard that makes relief work easier and faster. Most importantly, we created a solution that can genuinely save lives in real disaster scenarios.

What we learned

We learned how to combine multiple AI models—Whisper, GPT, and image generation—into a smooth, automated workflow using Base44. We also learned how to design systems that work for users with low literacy, low connectivity, and high stress. Building RELIEF-AI taught us the importance of clean data extraction, reliable map visualization, and meaningful UI during emergencies.

What's next for RELIEF-AI

Next, we plan to add automatic GPS detection, offline reporting options, support for more Indian languages, and collaboration tools for NGOs. We also aim to partner with local disaster management authorities to run real-world pilots. In the future, RELIEF-AI can become a national-level platform that provides fast, inclusive, and intelligent disaster reporting across India.

Built With

• base44