Nagrik

Nagrik: Voice first AI helping rural Indians access gov schemes. Users speak in local dialects to auto-fill forms and fetch DigiLocker docs. No typing, no middlemen. Bridging the digital divide

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The team formed around a shared goal: building Nagrik, a voice-first, vernacular AI assistant designed to make government services accessible for users with low literacy, limited digital skills, or age-related barriers.

What Nagrik Does

Nagrik streamlines public-service access through spoken interaction:

Voice-to-Scheme Matching: Users state their needs, and the system maps them to relevant government schemes.

“Fill-for-Me” Engine: Conversational prompts replace form-filling, auto-populating fields from verbal responses.

DigiLocker Integration: Required documents (Aadhaar, Ration Card, etc.) are fetched automatically, eliminating the need for scanning or uploading.

How We Built It

The team divided responsibilities according to technical strengths:

Full Stack & UI/UX: Krish handled full-stack development and interface design, creating an accessible, low-cognitive-load experience tailored to elderly users.

Research & System Stability: Avinash conducted field-focused research on rural digital barriers and refined system reliability through debugging and flow corrections.

Data Logic & Frontend Support: Akshar developed the data-processing pipeline and contributed to frontend refinement to ensure clarity and usability.

Challenges

Remote Collaboration: The team worked entirely across states, relying on digital coordination under tight timelines.

UX for Non-Technical Users: Designing an interface usable without digital familiarity required rethinking conventional UI logic.

Accomplishments

Structured Problem Breakdown: A six-chapter analytical framework guided development before any code was written.

Robust Prototype: The team produced a functional frontend and a solid logic layer comparable to advanced hackathon submissions.

Effective Collaboration: Clear division of responsibilities enabled rapid progress despite the staggered team formation.

What We Learned

Practical Full-Stack Python: Moving from academic familiarity to building a production-style pipeline.

Human-Centered Design: UX decisions made with dignity and simplicity as priorities.

Team Resilience: Strong coordination proved more decisive than prior experience or individual skill levels.

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