AI data marketplace
Browse a large marketplace of off-the-shelf datasets across speech, text, image, video, and multimodal formats. The site says datasets are searchable with advanced filters and can be customized to project requirements.
Defined.ai is an enterprise AI training data platform with a marketplace of ready-to-use datasets and custom services for data collection, annotation, and evaluation. It supports speech, audio, image, video, text, and multimodal workflows for teams building machine learning and generative AI systems.
Defined.ai is an AI training data platform for enterprise teams that need datasets and services for machine learning and generative AI. The site combines a marketplace of ready-to-use datasets with custom data collection, annotation, and evaluation services.
Its offering covers speech, audio, image, video, text, and multimodal data. The company emphasizes human-in-the-loop workflows, secure handling, and compliance-focused operations, with datasets and services designed for organizations that need quality and scale rather than one-off consumer tools.
Browse a large marketplace of off-the-shelf datasets across speech, text, image, video, and multimodal formats. The site says datasets are searchable with advanced filters and can be customized to project requirements.
Order custom data collection for speech, audio, image, video, and multimodal projects. Defined.ai positions this as secure, ethical collection with global diversity and enterprise quality controls.
Use model-in-the-loop annotation services for image, audio, text, video, and multimodal datasets. The annotation page emphasizes human validation, scalability, and quality control.
Run data evaluation and model evaluation to validate datasets and benchmark performance. The homepage describes these services as part of the AI lifecycle from data sourcing to deployment.
Access datasets through secure delivery methods such as API or file transfer. The source also mentions real-time progress monitoring for annotation work.
Work with a multilingual contributor base spanning more than 150 countries and 500+ languages, dialects, and locales. The company describes this as useful for diverse data needs and market expansion.
Build or fine-tune speech systems with datasets and annotation support for ASR, transcription, speaker diarization, and related language tasks.
Prepare image and video data for computer vision models using bounding boxes, segmentation, classification, tracking, and captioning workflows.
Source multilingual data for expansion into new markets, including language- and locale-specific datasets and contributor coverage across many countries.
Support regulated workflows in healthcare, finance, and other sensitive domains with security, compliance, and controlled data handling.
Collect and annotate multimodal data for robotics and other cross-modal systems that combine sensor, image, audio, and text inputs.
Defined.ai provides AI training data services and a data marketplace for enterprise teams. The source materials show support for custom data collection, annotation, and evaluation across speech, audio, image, video, text, and multimodal datasets.
The site describes a data marketplace with off-the-shelf datasets and a services offering for custom collection, annotation, and evaluation. Datasets can be accessed via secure delivery methods, including API for marketplace data and file transfer or API for training workflows.
Defined.ai presents its services as enterprise-grade and supports human-in-the-loop workflows, secure handling, and compliance-oriented processes. The source explicitly mentions ISO 27001, 27701, and 42001 accreditation, plus GDPR and HIPAA compliance.
The source indicates quote-based engagement rather than published pricing. The pricing page returns a 404, while the dataset flow mentions requesting quotes and free samples.
The site highlights use across healthcare, finance, automotive, content moderation, robotics, and conversational AI. It is positioned for teams that need multilingual, multimodal data and expert annotation at scale.