Use case
Text generation
Create coherent and contextually relevant text based on input prompts for creative and engaging content using Labelbox.
Trusted by companies of all sizes for text generation — from startups to Fortune 500s
Why Labelbox for text generation
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 solutions
Building AI applications with Text Generation
Create general and task-specific models with training data augmentation through text generation for NLP tasks.
Using AI
Using AI applications with Text Generation
Use text generation models to facilitate real-world applications such as content creation and language translation.
Boost your AI workforce
Access data labeling services with specialized text generation experience 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.
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.
