What is Defined.ai?
Defined.ai is a pioneering platform in the ethical AI data space, offering the world's largest marketplace for training datasets. Founded in 2015 by Dr. Daniela Braga, the company has secured $81M in funding and established itself as a global leader in providing high-quality, ethically sourced data for AI applications.
The platform offers comprehensive data solutions across multiple domains, including speech recognition, NLP, healthcare, and computer vision. Their offerings include scripted monologue datasets, spontaneous dialogue collections, medical image analysis data, and specialized content for various industry sectors. The company maintains rigorous quality control standards and provides both off-the-shelf and customizable dataset solutions to meet specific project requirements.
Features
- Ethical Data Collection: Transparent and responsible data sourcing practices
- Diverse Dataset Categories: Coverage across speech, NLP, healthcare, and computer vision
- Quality Assurance: Expert review and refinement of datasets
- Customization Options: Flexible dataset modification capabilities
- Multilingual Support: Data available in multiple languages and regions
- Expert Support: Access to AI professionals for project guidance
Use Cases
- Speech Recognition Development
- Medical Image Analysis
- Content Moderation
- Language Model Training
- Conversational AI Development
- Healthcare AI Solutions
- Machine Translation Projects
- Sentiment Analysis Training
FAQs
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What types of datasets are available on Defined.ai?
Defined.ai offers datasets across multiple categories including scripted monologue, spontaneous dialogue, IVR, NLP, medical images, podcasts, healthcare Q&A prompts, and adult content classification imagery. -
How does Defined.ai ensure data quality?
The platform employs expert teams to review and refine datasets rigorously, ensuring accuracy and maintaining top-quality standards for reliable AI project outcomes. -
What makes Defined.ai's data collection ethical?
The company maintains high ethical standards in data collection and management, ensuring transparency in their processes while prioritizing privacy and trust of clients and data contributors.
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