Sentiment Analysis

Translate emotions into insights with AI-powered Sentiment Analysis

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Overview

The Sentiment Analysis solution enables you to understand the true feelings of your customers based on reviews, support tickets, social posts, and feedback forms. Whether you need to track the perception of your brand, monitor complaints, or understand user experience better, we provide accurate and fast AI-powered insights into the tone, emotion, and intent behind your users across multiple Indian languages.

With built-in sarcasm detection, emotion tagging, and domain tuning, it doesn't just tell you the "what" behind your users' words, but also the "how."

Pricing

To know more about the SKUs and pricing click below.

Core Features at a Glance 

Multi-Class Sentiment Detection
Labels input as positive, negative, neutral, or mixed sentiment.
Indian Language + Code-Mixed Support
Handles inputs in English, Hindi, Tamil, Bengali, and other Indian languages - even when they’re mixed.
Real-Time & Batch Processing
Run sentiment checks on-the-fly or analyse large datasets offline.
Domain-Specific Tuning
Optimized for use cases in retail, banking, healthcare, and public sentiment monitoring.
Dashboard & API Ready
Feeds sentiment scores to your analytics tools or live dashboards through APIs.

What You Get

Understand Your Customers Better
See how people really feel about your services, products, or campaigns.
Act Fast on Negative Feedback
Identify and respond to dissatisfaction early - before it escalates.
Language-Ready for India
Go beyond English - analyze emotion in regional languages and code-mixed inputs.
Smarter Decisions, Backed by Data
Equip your marketing, support, and CX teams with emotional intelligence they can act on.

Still have questions?

English, and 10+ Indian languages - Hindi, Tamil, Bengali, Telugu, Marathi, etc. - and mixed language content.
Yes. It will analyse both short and long-form content.
Yes, you can have fine-grained emotion tags which will give you insights that extend beyond just "positive" or "negative".
Yes. With aspect-based sentiment you will know what users liked - or didn't like - about specific things like delivery time or pricing.
It has been trained on contextual language patterns and uses advanced NLP technology to minimize errors in interpretation of a sarcastic or negated phrase

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