AI That Actually Understands India
Advanced sentiment, emotion, and context analysis powered by Vaak 1 - trained on Indian social media data to understand sarcasm, regional dialects, Hinglish, and cultural nuance that generic models miss.
98%
Sentiment Accuracy
20+
Indian Languages
6
Emotion Categories
500+
Dialects Understood
Analysis built for India's complexity
Generic AI misses sarcasm, dialects, and code-switching. Vaak 1 does not.
Multilingual Sentiment
Accurate positive, negative, and neutral classification across Hindi, Tamil, Bengali, Marathi, Hinglish, and 16+ more languages.
Emotion Detection
Go beyond sentiment to detect joy, anger, fear, surprise, trust, and anticipation within social content.
Sarcasm & Irony Recognition
Vaak 1 is trained on Indian social media patterns and correctly interprets sarcasm that trips up generic AI models.
Context-Aware Classification
Understands brand mentions in context - distinguishing customer complaints from brand mentions in news, memes, and satire.
Topic Clustering
AI groups related mentions into topics automatically - no manual tagging required - revealing what themes drive conversation.
Intent Analysis
Classify content by intent: purchase intent, complaint, praise, query, or competitive comparison for sharper action.
Deep analysis, delivered in seconds
Three steps from raw mention to actionable insight - fully automated.
01
Ingest Raw Mentions
Every mention captured by Awshar AI is automatically queued for analysis - no manual tagging or spreadsheet uploads needed.
02
India-Trained Models Analyse
Our NLP models, trained on 20+ Indian languages and regional dialects, classify sentiment, detect emotions, extract entities, and score context - all simultaneously.
03
Structured Insights Ready
Results land in your dashboard as structured data: sentiment scores, emotion breakdowns, topic clusters, and entity graphs you can filter, compare, and export.
Trusted by teams making data-driven decisions
From consumer brands to research agencies - see how different teams put AI analysis to work.
Customer Insights Teams
Map emotional responses to product announcements, pricing changes, and new features across every major platform and language.
Crisis Communication Teams
Detect when negative sentiment is accelerating - across Hindi, English, and regional languages simultaneously - and get ahead of it.
Research & Strategy
Export structured sentiment time-series data into your BI tools for campaign performance reporting and brand health dashboards.
Common questions about AI Analysis
What Indian languages does the analysis support?
Our models are trained on 20+ languages including Hindi, Tamil, Telugu, Kannada, Bengali, Marathi, Gujarati, Punjabi, and Hinglish code-mixed text. Accuracy is above 95% across all supported languages.
Does sentiment analysis work on images and videos?
Currently our analysis covers text content, including captions and comments on video posts. Audio/video transcript analysis is on our roadmap.
How is context-aware analysis different from basic sentiment?
Basic sentiment labels text as positive or negative. Context-aware analysis understands sarcasm, irony, mixed sentiment within a sentence, and domain-specific language - reducing false positives significantly.
Can I define custom sentiment categories?
Yes. Enterprise plans allow you to define custom sentiment tags (e.g. Complaint, Praise, Query, Suggestion) and train the model on your brand-specific vocabulary.
Analysis is just the start
Explore the features that work alongside AI Analysis to complete the picture.
Mention Tracking
Feed the analysis engine with real-time mentions from 500+ sources across 7+ platforms.
Learn moreReal-time Sentiment Tracking
See sentiment scores update live on a dashboard built for always-on brand monitoring.
Learn moreAI Recommendation
Let AI turn analysis results into prioritised action cards for your team.
Learn moreSee what your audience really feels
Analyse millions of social conversations with AI that understands India.