Building Trust with Multilingual Sentiment Analysis
Generic sentiment tools often fail in India. Sarcasm, code-mixing, and regional expressions can flip “positive” and “negative” when you only rely on translation.
Awshar AI uses models trained on Indian languages and dialects. That means we capture context: when “bohot hard” means “very difficult” in one context and “very cool” in another, we get it right.
Accurate sentiment isn’t just a nice-to-have-it drives product decisions, campaign tweaks, and crisis response. Multilingual sentiment you can trust starts with data that was built for India.
Read Next
The Expanding Scope of Social Listening: From Tool to Infrastructure
Social listening began as a marketing add-on. It is becoming decision infrastructure — the layer institutions use to see reality before it's officially reported. Here's why the scope keeps expanding.
Social ListeningWhy Emotion in Social Listening Needs Three Points of View
Anger, joy, and every other emotion in social data mean different things depending on whose side you're reading from. Here's why social listening needs a three-sided lens — brand, competitor, and public.