An AI-powered multilingual voice assistant app that lets SC beneficiaries use voice conversations to get personalized skill training and livelihood recommendations.
Ministry of Social Justice and Empowerment (MoSJE) · Department of Social Justice and Empowerment · Software
Signing in saves it for your whole team — everyone on your invite link sees the same two entries. Anything you shortlisted while signed out comes with you.
Decomposed from what the description asks for. Nothing added.
Voice Interaction Interface
Supports regional languages and local dialects for natural, empathetic voice conversations.
Deployment Channels
Functions via IVR phone calls, WhatsApp voice notes, and lightweight mobile or kiosk interfaces.
Beneficiary Profiling Engine
Collects educational background, family occupations, skills, interests, and constraints using AI.
NSQF Recommendation System
Analyzes profiles using AI to recommend suitable NSQF-aligned training programs and employment opportunities.
Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.
The jury will check if the voice assistant actually supports regional languages and dialects, handles low-connectivity environments through IVR or WhatsApp, and accurately matches user profiles to NSQF-aligned training programs.
A jury can still ask about these. Decide them deliberately rather than by accident.
Generated from the brief's own wording and the competition's published rules — never from a guess about what this ministry prefers.
Which specific regional languages and dialects must be supported?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
What specific accuracy rate is expected for the AI recommendation matching?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Which IVR or telephony service provider APIs should be integrated?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Has any part of this been shown at a previous event, hackathon or college project?
The guidelines are explicit: your solution must not have appeared in any previous event or programme, of any sort. A recycled project is what a team under time pressure reaches for.
Each one is quoted from a gap in the brief, not a guess about your team.
No measurable target
The description never states a quantitative success metric or minimum accuracy percentage for the livelihood matching and skill recommendations.
What the organisers attached, and what the brief assumes you can get.
Same organisation, same year. Reading two of theirs tells you more about what they care about than reading one.
Pick what you are about to do and copy the prompt. It carries the organisers' own wording, the constraints they never spell out, and an instruction not to invent requirements they never set.
Who has this problem, what already exists, and what you would have to find out.
The brief asks for voice interaction interface. How would you build that?
Decoded from SIH26097 itself — Supports regional languages and local dialects for natural, empathetic voice conversations. The brief asks for it by name.
The brief asks for deployment channels. How would you build that?
Decoded from SIH26097 itself — Functions via IVR phone calls, WhatsApp voice notes, and lightweight mobile or kiosk interfaces. The brief asks for it by name.
The brief asks for beneficiary profiling engine. How would you build that?
Decoded from SIH26097 itself — Collects educational background, family occupations, skills, interests, and constraints using AI. The brief asks for it by name.
The brief asks for nsqf recommendation system. How would you build that?
Decoded from SIH26097 itself — Analyzes profiles using AI to recommend suitable NSQF-aligned training programs and employment opportunities. The brief asks for it by name.
Where does your data come from — a published source, one you collect, or one you generate?
No dataset is attached to this problem statement, so sourcing it is part of the work and nobody told you that.
Why not use what already exists? Name the closest thing to this that is already running.
A team that has not named the alternative themselves is answering this for the first time in the room.
Which single thing will you demonstrate end to end, start to finish, with nothing skipped?
Ours, not a rule: a narrow thing that fully works survives questioning better than a broad thing that half works. If nobody on the team can name it, that is the finding.
Show me this working: the jury will check if the voice assistant actually supports regional languages and dialects, handles low-connectivity environments through IVR or WhatsApp, and accurately matches user profiles to NSQF-aligned training programs.
This is the evaluator read for your problem statement, decoded from the brief's own wording.