See what happens next.
Then test what to do.
Audience and narrative intelligence for Indian public discourse, across seven platforms, in Hindi, Hinglish and English.
Arjun
Backend & agents
Brijesh
Collectors & pipeline
Divyanshu
Web client
Ravi
Analytics & forecasting
Bhavna
Design & landing page
Shreya
Labelling & evaluation
platforms
breakout levels
signals per post
minimum segment size (k)
[01]How it works
Agents plan and explain. Code collects and counts.
Collectors pull public posts into one shape, the labeller and embeddings read them, narratives and breakout scores are computed, and agents write the report around numbers they cannot invent.
Public sources
Collect
read-only · time-stamped
- One post shape for every platform
- Backfill, then live polling
- Coverage reported honestly per platform
Understand
labeller · embeddings
- Sentiment, emotion, sarcasm, stance
- Language, script and place per post
- 384-dim multilingual vectors
Score
narratives · breakout · forecast
- Cross-lingual narrative clusters
- Breakout Level 1–6 with why-chips
- Forecast cones with backtest error
Agents write the report
Clarifier
narrows the ask
Platform
one per platform
Fusion
assembles blocks
Copilot
answers follow-ups
agents narrate · never write a number that is not in a tool result
Every figure carries a result id. Click it and the posts behind it open in a drawer.
Sentiment, emotion, sarcasm and stance are separate. "Glad he got arrested" is positive and against.
Hindi, Hinglish and English posts making the same claim cluster into one narrative.
How far a story has travelled from the community it started in, not how loud it is.
A Sankey shows which audience carried a story to which other audience, hour by hour.
Synchronised posting, shared links and copypasta clusters are scored and shown alongside the posts.
Demographics are shown per segment, never per person, and hidden below 20 people.
Every search, simulation and brief is written to a SHA-256 linked log.
[02]Product
Four ways in. One brain behind them.
Ask a question, watch what is rising, investigate a narrative, then test what to do about it.
Ask
Ask anything
Type a topic. A clarifier narrows it with option chips, per-platform agents start collecting, and a live report streams in block by block.
Open the web app
Watch
What is breaking out
Always-on collection over an India watch universe. Narratives ranked by Breakout Level with why-chips, forecasts and alerts.
Investigate
Investigate a narrative
Mood over time, who carries it, spread between communities, cascade replay, coordination detection and matched fact-checks.
Act
The Counter-Message Lab
Draft up to three responses, simulate each on the real audience graph, compare against doing nothing, and see backfire risk before you send. Export the whole investigation as a brief.
Brief
One click to a brief
Timeline, network, actors, evidence and assessment, exported as a PDF with every figure sourced.
[03]Features
Built for the five things the problem statement asks for
Continuous collection, nuanced sentiment, aggregate demographics, trend prediction and link analysis — each one clickable down to the posts underneath it.
bahut badhiya, ab to relief fund bhi gayab. wah kya system hai 👏
romanised Hindi · praise words, hostile meaning
Four signals, scored apart
Sentiment, emotion, sarcasm and stance in Hindi, Hinglish and English. Praise words can still be an attack.
Seven platforms, one shape
Telegram, WhatsApp, X, Instagram, YouTube, Reddit and news land as the same time-stamped post.
Breakout Level 1–6
Ranked by how far a narrative has escaped its own community, with chips that say why.
Assam local-news
4,180 accounts
national politics
27,400 accounts
who carried it across, and at what hour
Spread between communities
Which audience carried a story to which other audience, and the bridge accounts that did it.
Every number opens its posts
Each figure is stored with a result id. Click it and the exact posts behind it appear.
no caste or religion inference, ever
Aggregate only, k ≥ 20
Demographics per segment with uncertainty. Small segments stay hidden. No per-person profiles.
23 accounts within 90 seconds
Coordination, with evidence
Synchronised posting, shared links and copypasta clusters, shown next to the posts that triggered them.
Built with
[04]FAQ
Common questions
Public posts and comments from Telegram, WhatsApp, X, Instagram, YouTube, Reddit and news plus fact-check feeds. Collection is read-only: the accounts we collect with never post, reply, like or follow.
Smart India Hackathon 2026 · SIH26152 · Social Media Analytics · NTRO
See it on live Indian discourse.
Open Sarvagya and ask your first question.
Public data only · aggregate demographics, k ≥ 20 · no true-or-false verdicts · every number traces to its posts