Daniela Braga
Founder
Defined.ai
Defined.ai provides a marketplace for ethically sourced training data, specializing in diverse datasets for speech recognition, natural language processing, and medical image analysis. The company addresses the need for high-quality, bias-free data that complies with ethical and legal standards, enabling organizations to develop AI solutions responsibly and effectively.
- Artificial Intelligence
- Data & Analytics
- Developer Tools
- Software Only
Updated today
Funding
Raised to date
$81.9MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Funding rounds are not available yet.
Founders
Product
Problem
Organizations developing AI solutions often struggle to find high-quality, ethically sourced training data that is free from bias and complies with legal standards. The lack of diverse and representative datasets can lead to skewed AI models and unfair outcomes.
Solution
Defined.ai offers a marketplace for ethically sourced AI training data, providing diverse datasets for speech recognition, natural language processing, computer vision, and more. The platform ensures data is collected and managed with high ethical standards, prioritizing transparency, privacy, and fairness. Datasets are rigorously reviewed and refined by an expert team to ensure accuracy and meet top-quality standards. Defined.ai also provides customizable off-the-shelf datasets that can be tailored to specific project requirements, along with custom data services and expert support.
Target Audience
The primary customers are AI developers, machine learning engineers, and data scientists seeking high-quality, ethically sourced training data to build and improve AI models.
Features
- Marketplace offering diverse, off-the-shelf datasets for various AI applications, including speech, NLP, and computer vision.
- Ethically sourced data collected with transparent practices, ensuring responsible and fair AI development.
- Customizable datasets that can be sliced and tailored to align with specific project goals.
- Rigorous quality control processes, including expert review and refinement, to ensure accuracy and reliability.
- Support for multiple data types, including scripted and spontaneous speech, podcasts, medical images, and adult content classification imagery.
- Datasets available in multiple languages to support multilingual AI applications.