WIRESTOCK

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GDPR
Compliant
20+
Image Categories
4.5M
Images
Used By
Adobe
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WIRESTOCK Data Products: APIs & Datasets

Explore WIRESTOCK’s datasets, databases, and data feeds.
Wirestock's AI/ML Image Training Data, 4.5M Files with Metadata: This data product offers a vast collection of images and associated meta...
4.5M images
100% Image attachment
249 countries covered
5 years of historical data

WIRESTOCK Pricing & Cost

Learn about WIRESTOCK’s prices, subscription cost, and API pricing.

Wirestock currently has 4.5M photos and videos in 20+ categories. We offer various pricing options from licensing the entire dataset to offering categories separately. The pricing depends on the size of the dataset and duration of the license. The rate per image is in the range of $0.03-$0.10.

The supported pricing models for WIRESTOCK’s data are available by getting in contact with them via Datarade. Get talking to a member of the WIRESTOCK team to receive custom pricing options, information about data subscription fees, and quotes for WIRESTOCK’s data offering tailored to your use case.

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About WIRESTOCK

Learn more about WIRESTOCK’s data sources, use cases, and integrations.

WIRESTOCK in a Nutshell

Wirestock is a revolutionary platform that simplifies the process of selling digital content online.

Founded in 2018, the company has grown rapidly and now boasts a team of dedicated professionals who are passionate about helping creators monetize their work.

Wirestock’s unique model allows creators to upload their content to the platform, which then distributes it across multiple online marketplaces.

This streamlined process eliminates the need for creators to manage multiple accounts and track sales on different platforms, saving them time and effort. The company’s core offering is a vast and diverse dataset of 4.5 million files, including images, videos, and AI art, which is ideal for AI/ML training.

Headquarters
Armenia

Country Coverage

Africa (58)
Algeria
Angola
Benin
Botswana
Burkina Faso
Burundi
Cabo Verde
Cameroon
Central African Republic
Chad
Comoros
Congo
Congo (Democratic Republic of the)
Côte d'Ivoire
Djibouti
Egypt
Equatorial Guinea
Eritrea
Ethiopia
Gabon
Gambia
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Liberia
Libya
Madagascar
Malawi
Mali
Mauritania
Mauritius
Mayotte
Morocco
Mozambique
Namibia
Niger
Nigeria
Rwanda
Réunion
Saint Helena, Ascension and Tristan da Cunha
Sao Tome and Principe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
South Sudan
Sudan
Swaziland
Tanzania, United Republic of
Togo
Tunisia
Uganda
Western Sahara
Zambia
Zimbabwe
Asia (51)
Afghanistan
Armenia
Azerbaijan
Bahrain
Bangladesh
Bhutan
Brunei Darussalam
Cambodia
China
Cyprus
Georgia
Hong Kong
India
Indonesia
Iran (Islamic Republic of)
Iraq
Israel
Japan
Jordan
Kazakhstan
Korea (Democratic People's Republic of)
Korea (Republic of)
Kuwait
Kyrgyzstan
Lao People's Democratic Republic
Lebanon
Macao
Malaysia
Maldives
Mongolia
Myanmar
Nepal
Oman
Pakistan
Palestine, State of
Philippines
Qatar
Saudi Arabia
Singapore
Sri Lanka
Syrian Arab Republic
Taiwan
Tajikistan
Thailand
Timor-Leste
Turkey
Turkmenistan
United Arab Emirates
Uzbekistan
Vietnam
Yemen
Europe (51)
Albania
Andorra
Austria
Belarus
Belgium
Bosnia and Herzegovina
Bulgaria
Croatia
Czech Republic
Denmark
Estonia
Faroe Islands
Finland
France
Germany
Gibraltar
Greece
Guernsey
Holy See
Hungary
Iceland
Ireland
Isle of Man
Italy
Jersey
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia (the former Yugoslav Republic of)
Malta
Moldova (Republic of)
Monaco
Montenegro
Netherlands
Norway
Poland
Portugal
Romania
Russian Federation
San Marino
Serbia
Slovakia
Slovenia
Spain
Svalbard and Jan Mayen
Sweden
Switzerland
Ukraine
United Kingdom
Åland Islands
North America (13)
Belize
Bermuda
Canada
Costa Rica
El Salvador
Greenland
Guatemala
Honduras
Mexico
Nicaragua
Panama
Saint Pierre and Miquelon
United States of America
Oceania (25)
American Samoa
Australia
Cook Islands
Fiji
French Polynesia
Guam
Kiribati
Marshall Islands
Micronesia (Federated States of)
Nauru
New Caledonia
New Zealand
Niue
Norfolk Island
Northern Mariana Islands
Palau
Papua New Guinea
Pitcairn
Samoa
Solomon Islands
Tokelau
Tonga
Tuvalu
Vanuatu
Wallis and Futuna
Other (9)
Antarctica
Bouvet Island
British Indian Ocean Territory
Christmas Island
Cocos (Keeling) Islands
French Southern Territories
Heard Island and McDonald Islands
South Georgia and the South Sandwich Islands
United States Minor Outlying Islands
South America (42)
Anguilla
Antigua and Barbuda
Argentina
Aruba
Bahamas
Barbados
Bolivia (Plurinational State of)
Bonaire, Sint Eustatius and Saba
Brazil
Cayman Islands
Chile
Colombia
Cuba
Curaçao
Dominica
Dominican Republic
Ecuador
Falkland Islands (Malvinas)
French Guiana
Grenada
Guadeloupe
Guyana
Haiti
Jamaica
Martinique
Montserrat
Paraguay
Peru
Puerto Rico
Saint Barthélemy
Saint Kitts and Nevis
Saint Lucia
Saint Martin (French part)
Saint Vincent and the Grenadines
Sint Maarten (Dutch part)
Suriname
Trinidad and Tobago
Turks and Caicos Islands
Uruguay
Venezuela (Bolivarian Republic of)
Virgin Islands (British)
Virgin Islands (U.S.)

Data Offering

Wirestock’s core offering is a rich and diverse dataset of 4.5 million files, including high-quality images, videos, and AI art. This dataset is ideal for AI/ML training, providing real-world visual insights across 20 distinct categories. Our data is GDPR-compliant and comes with detailed metadata, making it a valuable resource for a wide range of applications, from computer vision to content personalization.

Use Cases

Wirestock’s image database is a rich resource that can be leveraged in numerous ways. Here are five key use-cases where our data can provide significant value:

AI/ML Training: Our dataset is an excellent resource for training AI and Machine Learning models, particularly in the field of computer vision. The extensive variety of images, coupled with detailed metadata, provides a comprehensive training set for models learning to recognize and interpret visual elements. For instance, a model trained on our data could be used in surveillance systems to identify specific objects or individuals, or in autonomous vehicles to recognize road signs and pedestrians.

Content Personalization: In the era of personalized experiences, our data can be a game-changer for e-commerce platforms and online publishers. By analyzing user behavior and preferences, these platforms can use our images to display visually appealing and relevant content to their users. For example, a travel website could use images from our ‘Nature’ or ‘Buildings/Landmarks’ categories to personalize recommendations based on a user’s past browsing history or stated preferences.

Visual Search Engines: Our dataset can significantly enhance the accuracy of visual search engines. By training on our diverse set of images, these engines can better understand and match user queries with relevant results. For example, a user could upload a photo of a dress they like, and the search engine, trained on our ‘Fashion/Apparel’ images, could find similar items available for purchase.

Advertising and Marketing: Our images can be used to create more engaging and visually appealing campaigns. With our wide range of categories, advertisers and marketers can find the perfect image for any context. For instance, a marketing agency could use images from our ‘Technology’ category for a tech startup’s ad campaign, ensuring the visuals align with the brand’s identity and message.

Educational Tools: Our dataset can be used to create visual aids for learning in educational tools. For instance, language learning apps could use our images to help students associate words with their visual representations. A student learning the word ‘beach’ could be shown an image from our ‘Nature’ category, reinforcing their understanding of the term.

Each of these use-cases leverages the diversity, quality, and detailed metadata of our dataset, demonstrating its wide-ranging applicability and value.

Artificial Intelligence (AI)
Data-Efficient Machine Learning
Machine Learning (ML)

Data Sources & Collection

Our data is sourced directly from creators who upload their content to our platform. We have a rigorous quality control process to ensure the data’s accuracy and relevance. Each file is accompanied by detailed metadata, including title, description, and keywords, which are provided by the creators. This user-generated approach ensures a constant influx of fresh, diverse, and authentic data, making our dataset a dynamic and continually evolving resource.

Key Differentiators

User-Generated Content: Our data is sourced directly from creators who upload their content to our platform. This user-generated approach ensures a constant influx of fresh, diverse, and authentic data. Unlike datasets that are scraped from the web or generated synthetically, our data reflects real-world visual insights from a wide range of perspectives. This makes our dataset a dynamic and continually evolving resource.

Quality Control: We have a rigorous quality control process in place. Each file that is uploaded to our platform is reviewed to ensure it meets our high standards for quality and relevance. This ensures that our clients receive only the best data for their AI/ML training needs.

Detailed Metadata: Each file in our dataset comes with detailed metadata, including a title, description, and keywords. This metadata is provided by the creators themselves, ensuring it accurately reflects the content of the file. This level of detail is invaluable for training AI/ML models, as it provides additional context that can help improve the accuracy of the model.

GDPR Compliance: We take data privacy seriously. All of our data is GDPR-compliant, meaning it meets the stringent privacy standards set by the European Union. This gives our clients peace of mind knowing that they can use our data without worrying about privacy issues.

Wide Range of Categories: Our dataset covers 20 distinct categories, from Animals/Wildlife to Technology and Transportation. This wide range of categories ensures a diverse training set for AI/ML models, improving their ability to recognize and understand various visual elements.

Ease of Use: Our platform is designed to be user-friendly and easy to navigate. Clients can easily access and download the data they need. We also offer excellent customer support to assist clients with any questions or issues they may have.

Community Engagement: At Wirestock, we believe in the power of community. We have a vibrant community of creators who are passionate about their work. We regularly engage with our community through various initiatives, fostering a sense of camaraderie and mutual support. This community-driven approach not only ensures a steady stream of new data but also helps us stay in tune with the needs and interests of our users.

In conclusion, Wirestock offers a unique combination of user-generated content, rigorous quality control, detailed metadata, GDPR compliance, a wide range of categories, ease of use, and community engagement. This makes us a preferred choice for clients seeking high-quality image data for AI/ML training.

Data Privacy

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Frequently asked questions about WIRESTOCK

What does WIRESTOCK do?

Wirestock is a platform where creators share and sell their images and videos. Our core data offering is a vast and diverse dataset of 4.5 million files, ideal for AI/ML training. We provide high-quality image data with metadata across 20 categories, empowering AI applications.

How much does WIRESTOCK cost?

The supported pricing models for WIRESTOCK’s data are available by getting in contact with them via Datarade. Get talking to a member of the WIRESTOCK team to receive custom pricing options, information about data subscription fees, and quotes for WIRESTOCK’s data offering tailored to your use case.

What kind of data does WIRESTOCK have?

Natural Language Processing (NLP) Data, Annotated Imagery Data, Machine Learning (ML) Data, and Deep Learning (DL) Data

What data does WIRESTOCK offer?

Wirestock’s core offering is a rich and diverse dataset of 4.5 million files, including high-quality images, videos, and AI art. This dataset is ideal for AI/ML training, providing real-world visual insights across 20 distinct categories. Our data is GDPR-compliant and comes with detailed metadata, making it a valuable resource for a wide range of applications, from computer vision to content personalization.

How does WIRESTOCK collect data?

Our data is sourced directly from creators who upload their content to our platform. We have a rigorous quality control process to ensure the data’s accuracy and relevance. Each file is accompanied by detailed metadata, including title, description, and keywords, which are provided by the creators. This user-generated approach ensures a constant influx of fresh, diverse, and authentic data, making our dataset a dynamic and continually evolving resource.

What are the best use cases for WIRESTOCK’s data?

Wirestock’s image database is a rich resource that can be leveraged in numerous ways. Here are five key use-cases where our data can provide significant value: AI/ML Training: Our dataset is an excellent resource for training AI and Machine Learning models, particularly in the field of computer vision. The extensive variety of images, coupled with detailed metadata, provides a comprehensive training set for models learning to recognize and interpret visual elements. For instance, a model trained on our data could be used in surveillance systems to identify specific objects or individuals, or in autonomous vehicles to recognize road signs and pedestrians. Content Personalization: In the era of personalized experiences, our data can be a game-changer for e-commerce platforms and online publishers. By analyzing user behavior and preferences, these platforms can use our images to display visually appealing and relevant content to their users. For example, a travel website could use images from our ‘Nature’ or ‘Buildings/Landmarks’ categories to personalize recommendations based on a user’s past browsing history or stated preferences. Visual Search Engines: Our dataset can significantly enhance the accuracy of visual search engines. By training on our diverse set of images, these engines can better understand and match user queries with relevant results. For example, a user could upload a photo of a dress they like, and the search engine, trained on our ‘Fashion/Apparel’ images, could find similar items available for purchase. Advertising and Marketing: Our images can be used to create more engaging and visually appealing campaigns. With our wide range of categories, advertisers and marketers can find the perfect image for any context. For instance, a marketing agency could use images from our ‘Technology’ category for a tech startup’s ad campaign, ensuring the visuals align with the brand’s identity and message. Educational Tools: Our dataset can be used to create visual aids for learning in educational tools. For instance, language learning apps could use our images to help students associate words with their visual representations. A student learning the word ‘beach’ could be shown an image from our ‘Nature’ category, reinforcing their understanding of the term. Each of these use-cases leverages the diversity, quality, and detailed metadata of our dataset, demonstrating its wide-ranging applicability and value.