Magic Data

MAGIc Data is a data-services company focused on the collection, annotation, and delivery of training and Testing datasets for Artificial Intelligence systems. Rather than selling a single end-user APPlication, it positions itself as a data partner for organizations building or refining models, offering industry-specific solutions that pAIr datasets with domain expertise. Its materials emphASIze quality, compliance, and SECurity as core priorities, which matters for teams working in regulated sectors or handling sensitive user Information.

What it does

The company assembles datasets and annotation services across several verticals. Customers can source labeled text, speech, and conversational data intended to improve model accuracy and robustness. Magic Data also frames its offerings around industry know-how, meaning the data packages are shaped around the terminology and use cases of a particular field rather than being generic corpora.

Key capabilities

• Training and test data provisioning: curated speech, text, and dialogue datasets for model development and evaluation.
• Annotation and labeling: support for NLP text labeling and related tasks used to tune interACTion systems.
• multilingual data handling: language resources that can support cross-market model work.
• Industry solutions: tailored packages for smart mobility and Autonomous Driving, Financial Services such as customer service and meeting transcription, social platforms with sentiment analysis and recommendation, smart home voice control, and smart terminal optimization.
• Compliance and security emphasis: positioning around data governance, which is often a procurement requirement in finance and automotive.

Who it is for

Magic Data is aimed at AI Engineering and data teams, not General consumers. Typical users include automotive groups refining in-cabin assistants or driving models, banks and financial firms improving automated Customer Service and transcription, social platfORM operators working on sentiment and recommendations, and hardware makers tuning voice control on connected devices. research groups needing labeled speech or text corpora may also find the catalog relevant, though availability varies by domain and language.

How to get started

Engagement generally begins through the company's website, where prospective CLIents describe their domain, language coveRAGe, data modality, and volume needs. From there, a scoping conversation typically determines whether an existing dataset fits or a custom collection and annotation project is required. Because much of the work is bespoke, Timelines depend on the size and complexity of the request.

Pricing and access

Magic Data operates primarily on a business-to-Business, quote-based model, so public per-unit prices are not consistently published and may vary by dataset size, language, and annotation depth. Some Sample or open resources may be available for eValuation. Teams should confirm licensing terms, usage restrictions, and delivery format directly, and treat any listed figures as indicative rather than final.