Top 12 Data Crowdsourcing Platform in 2025

With the spread of AI tools like generative AI and chatbots, the demand for AI data services has also increased. One such service is data crowdsourcing platforms, which leverage large groups to gather data, enhancing collection efforts with fast, detailed insights.

Here, we compare the best crowdsourcing platform to fulfill your AI data needs.

Top data crowdsourcing platforms on the market

This section compares the top crowdsourcing platforms on the market that offer data services on demand.

Table 1. Comparison based on platform features & capabilities criteria

• The companies are sorted according to the number of reviews in both tables, with the sponsored placed at the top.
• The comparison table is created from publicly available and verifiable data.
• The companies selected in this comparison were based on the relevance of their services. This means whether they offer data collection or generation services through a crowdsourcing platform.
• All vendors chosen in this comparison have 50+ employees.
• Apart from Surge AI, which only offers speech and text data, all companies cover a wide array of data types (Image, Video, Audio, Text, etc.).
• A company is assumed to follow a code of conduct if it has a code of conduct page on its website.

Table 2. Comparison based on vendor market presence & experience criteria

* Based on data from leading B2B review platforms.

** A company was considered to be data collection-focused if data collection was seen as the main offering on its website.

Figure 1. Crowd size comparison

• Innodata Inc. and TaskUS were not included since their crowd size was smaller than 100K.
• Some vendors were also excluded since their crowd size data was not found on their websites.

Here is the criteria we used for the comparison.

Data crowdsourcing platforms’ overview

This section provides an overview of each data crowdsourcing platform compared in this article. The section also offers some pros and cons of working with the platforms, including customer reviews from B2B review platforms. We also incorporate some external data on company-specific news to offer you a broader perspective on the company’s pros and cons.

1. Clickworker

Clickworker is a data crowdsourcing platform that breaks down large projects into micro-tasks and distributes them to a global network to complete. It specializes in tasks such as AI data collection, data annotation, data categorization, and web research. Here is a list of Clickworker’s data solutions:

• AI training data collection or generation (Done by humans)
• Image & video datasets (Different formats and specifications)
• Audio or speech datasets (Different languages and dialects)
• Text datasets
• Data annotation service
• Research/survey data collection
• Reinforcement learning from human feedback (RLHF)

Pros and cons of working with Clickworker:

• The company is suitable for small to large-scale projects.
• Its network of contributors is the largest among its competitors and is said to be reliable by previous customers.
• Its data annotation service is considered effective and scalable by previous customers.

Choose Clickworker for diverse crowdsourced datasets to train your AI models.

2. Appen

Appen also offers data services through a crowdsourcing platform. It offers services that include: 

• Data collection
• Data annotation
• Data validation

Pros and cons of working with Appen:

• Appen’s platform is consdiered as user-friendly and its data processing services are said to be affective.
• According to recent news, Appen’s performance has been declining as it loses clients and goes through financial losses.¹
• Some customers highlighted surver crashes on Appen’s platform.
• Appen is suitable for small to misdized projects due to its smaller network of participants.

3. Prolific

Prolific is another crowdsourcing platform that offers data services for various use cases. Organizations use it for AI data, academic research, and market research purposes. Learn about prolific alternatives here.

Here is a list of their offerings:

• AI data collection
• AI training and evaluation
• Academic research data
• Online survey participants

Pros and cons of working with Prolific

• Prolific does not offer data annotation as a service, rather it offers the option to pair your annotation tools.
• Some of Prolific’s workers were using AI tools to complete their tasks, based on previous customer reviews.
• Its research data collection service is more popular than its AI data services.

4. Amazon Mechanical Turk (MTurk)

Amazon Mechanical Turk, or MTurk, is a crowdsourcing platform and marketplace where businesses can outsource tasks and jobs to a network of workers who can perform these tasks virtually. Here is a list of their offerings:

• Data collection
• Data annotation
• Market research & surveys
• Academic research
• Other data services

Pros and cons of working with Amazon Mechanical Turk

• Its data collection service is considered to be quick, efficient, and user-friendly.
• The quality of its data projects is said to be low, by customers.
• It has a significantly smaller network of contributors, and most of the contributors lack English skills.

Learn about Amazon Mechanical Turk alternatives here.

5. Telus International

Telus International focuses on customer experience (CX) and digital IT solutions. While it has a wide range of offerings, it also offers data services through a crowdsourcing platform.

Pros and cons of working with Telus International

• It offers data annotation along with its AI data collection services
• AI data-related are not the main focus of Telus International. It mainly focuses on the customer experience domain.
• Some customers found Telus International’s data annotation service slow.

6. TaskUs

While TaskUS’s key offerings revolve around customer experience, it also offers the following AI services:

• Data collection
• Data annotation (image, video, audio, and text)
• Data for research

Pros and cons of working with TaskUS

• The company offers data collection and annotation as services of almost all data types.
• The crowd size is significantly smaller than that of other crowdsourcing platforms like Clickworker and Appen.
• The company’s main focus is not AI data collection/annotation.

7. Summa Linguae Technologies

Summa Linguae Technologies also operates through a crowdsourcing platform. Its offerings include:

• Data collection for AI models 
• Data annotation
• Data translation

8. LXT

Headquartered in Canada, LXT offers AI-driven data services through its crowdsourcing platform. It claims to help companies enhance their AI and machine learning projects by providing labeled data. The list of data services offered by LXT:

• Data collection
• Data evaluation
• Data annotation
• Data Transcription

Pros and cons

• Its services include AI data collection, annotation, and RLHF.
• It has a weak market presence, so potential customers can not evaluate its performance.
• It has a significantly smaller crowd size than other platforms.

9. Surge AI

Based in California, Surge AI provides training data for machine learning models through a crowdsourcing platform. Surge AI focuses on collecting and labeling data for Large language models (LLMS)

• AI data labeling and annotation
• AI Data collection
• And other human-generated data services

10. Toloka AI

Toloka AI is a crowdsourcing platform for collecting and improving AI training data. They provide various services such as data labeling, data cleaning, and data categorization to enhance machine learning models. 

Pros and cons of working with Toloka AI

• The company offers data collection and annotation of all data types (Image, video, text, audio).
• Toloka AI has a significantly smaller crowdsourcing platform with a network of around 200K, which is relatively smaller than its competitors.

11. Innodata Inc.

Based in New Jersey, Innodata Inc. offers various AI solutions through its crowdsourcing platform. Its solutions include data collection and annotation.

Pros and cons of working with Innodata Inc.

• The company offers a significantly smaller crowdsourcing platform as compared to its competitors. With a crowd size of only ~5000 workers.
• The company does not have a strong online presence, as we did not find any customer or worker reviews on B2B or B2C platforms.

12. DataForce by Transperfect

DataForce by TransPerfect offers data collection and annotation for AI and machine learning projects. They provide services like speech and natural language processing data, image and video annotation, and more. Their data services include:

• Data collection
• Data annotation
• Data transcription
• Data moderation

Pros and cons of working with DataForce

• A relatively larger crowd amongst the competitors. A network of over 1 million workers.
• Weak online presence. It is difficult to evaluate its performance since there are no customer reviews.

Comparison criteria for the data crowdsourcing platform

Choosing the right crowdsourcing platform for your AI projects is crucial for ensuring data quality and integrity. We divided the criteria into 2 categories: market presence and experience & platform capabilities. Here are the key criteria to consider:

Market presence & experience:

1. User ratings: This criterion ensures the importance of B2B platform reviews (e.g., G2, Trustradius, Capterra) for assessing the data crowdsourcing platform’s performance.
2. Number of reviews: High review counts indicate a large customer base and offer insights into customer satisfaction levels.
3. Founded: Older companies typically have more experience and may provide more refined services. So it is important to consider the age of the company. However, this is not always the case since some companies focus on a particular service, such as data collection, and gain more expertise in that domain in a shorter period of time.
4. Dataset diversity: This criterion ensures the importance of having a diverse crowd in gathering or generating data to ensure accuracy across various languages and dialects. You can see the crowd size comparison of all the companies in Figure 1.

Platform capabilities:

5. Data annotation services: This criterion covers the necessity of data annotation for machine learning models and the benefits of integrated annotation services.
6. Mobile & API integration: This criterion is for the significance of mobile app availability and API integration in data crowdsourcing platforms.
7. ISO 27001 certification: This criterion ensures the importance of data protection practices as indicated by ISO 27001 certification.
8. Code of conduct: This criterion is considered for the impact of the platform provider’s ethical practices on a business’s reputation.
9. Data types covered: The range of data types a platform offers, is crucial for specific applications like automated driving systems.

FAQs

External resources

• 1. Appen, which helps Amazon and Google train AI, is reeling. CNBC