Delhi and IIT Kanpur build AI grievance platform for unified citizen complaints

Delhi’s new grievance platform is a small but telling example of how generative and semantic AI are seeping into everyday governance. Instead of building yet another chatbot, the city is wiring machine learning into the back office: clustering and routing complaints, extracting text from scanned documents, and surfacing patterns in how departments respond. That’s closer to the kind of systems‑level, process‑aware AI that AGI proponents talk about than to single‑turn Q&A bots.([indianexpress.com](https://indianexpress.com/article/cities/delhi/faster-grievance-redressal-public-delhi-govt-set-platform-iit-kanpur-10445987/lite/?utm_source=openai))

Strategically, this project gives Indian researchers and officials a real, messy civic dataset to experiment with: millions of grievances rich in local language, politics and bureaucracy. If it works, it will demonstrate that AI can improve state capacity in areas citizens feel acutely—water, power, housing, services—without replacing humans, by acting as an always‑on triage and analysis layer. It also sets a blueprint for other Indian states and Global South cities: pair a strong technical institute with a motivated local government, then focus AI on unglamorous but high‑impact workflows. That practical, incremental pattern is likely to be one of the ways society actually learns how to govern more capable AI systems.