Attached Office

India Meteorological Department (IMD)

Five evidence-based challenges identified for this entity, each paired with a ready-to-build AI tool specification — free for the Government of India to deploy.

Top 5 Challenges

Drawn from official reports, audits, parliamentary material and public feedback. Framed as improvement opportunities, never as criticism.

1
Forecasts face last-mile dissemination gaps in local languages and formats
2
Nowcasting accuracy for extreme rainfall and urban flooding events needs improvement
3
Observation network gaps and sensor data quality issues affect model inputs
4
District-level agromet advisories need customization at scale for farmers
5
Public warnings need clearer impact-based communication to drive protective action

Five AI Tools

Each tool answers the matching challenge above, and is built on curated official sources with safeguards and human oversight.

Mausam Vaani

Multilingual Forecast Dissemination Engine

Turns IMD forecasts and warnings into last-mile messages in Hindi and regional languages for IMD offices, state disaster cells and broadcasters: auto-drafts localized bulletins, SMS/WhatsApp-ready texts and audio scripts matched to district audiences.

View build spec

Varsha Netra

Extreme Rainfall Nowcasting Assistant

Assists IMD nowcasting desks in interpreting radar, satellite and AWS feeds for extreme rainfall and urban flood risk: drafts 0-3 hour nowcast texts, cross-checks signal consistency, and highlights vulnerable urban zones for targeted alerts.

View build spec

Vedh Darpan

Sensor Network Quality Monitor

Monitors IMD's observation network for data quality: detects silent, drifting or biased AWS/ARG stations and gauges, ranks maintenance priorities, and quantifies how sensor gaps degrade model inputs and forecast quality for network planners.

View build spec

Fasal Doot

District Agromet Advisory Generator

Generates district- and block-level agromet advisories at scale for IMD and agriculture officers: fuses forecasts with crop stage and local practices to draft actionable, crop-specific guidance in regional languages for farmers under the GKMS programme.

View build spec

Chetavani Bodh

Impact-Based Warning Composer

Helps IMD and disaster agencies write impact-based warnings: converts hazard forecasts into who/what/where impact statements with clear protective actions, aligned to colour codes and NDMA guidance, so citizens act rather than ignore alerts.

View build spec

Are you from India Meteorological Department (IMD)?

We will build, deploy and hand over these five tools to your office free of charge, as a seva to the nation. No licence fee, no lock-in.

Contact the project team