Use case

Sentiment Analysis

Determine the emotional tone and opinion expressed in text data for valuable insights and informed decision making using Labelbox.

Sentiment Analysis

Trusted by companies of all sizes for sentiment analysis — from startups to Fortune 500s

Why Labelbox for sentiment analysis

Accelerate AI alignment

Combine model assisted labeling and human expertise to quickly prepare data for training, testing and validation.

Generate high quality datasets

Optimize custom labeling and review workflows to ensure the highest quality data for model training and fine-tuning.

Maintain data privacy & security

Keep full ownership, transparency, and control over your data throughout the AI development process.

Boost your AI expertise

Supercharge your data engine with the help of Labelbox AI experts and on demand labeling services.

Building AI applications with sentiment analysis

Building AI solutions

Building AI applications with sentiment analysis

Train highly accurate sentiment analysis models for real-world applications to understand customer opinions and enhance brand reputation.

Automate using sentiment analysis foundation models

Using AI

Automate using sentiment analysis foundation models

Automatically categorize and analyze opinions using foundation models to perform sentiment analysis.

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Boost your AI workforce

Boost your AI workforce

Access data labeling services with specialized sentiment analysis expertise and more to match your use cases. Collaborate with the workforce in real-time to maintain high data quality while keeping human labeling costs to a minimum using AI and automation techniques.

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Customer spotlight

Dialpad, a leading AI-powered customer intelligence platform company used fine-tuning to build a powerful LLM over five years via five billion minutes of business conversations. The model offers out of the box capabilities to businesses to accurately summarize business calls, extract important insights and offer in-the-moment coaching to sellers and customer reps. Advanced discovery, curation, and annotation capabilities were crucial for building high-quality training datasets. Human evaluation was also critical to ensure quality outcomes before the system was turned live. Labelbox enabled this organization to accelerate the creation of the LLM by 75% through rich, integrated capabilities for data preparation and human evaluation.