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Top 12 Data Crowdsourcing Platform: Evaluation & User Reviews

Top 12 Data Crowdsourcing Platform: Evaluation & User ReviewsTop 12 Data Crowdsourcing Platform: Evaluation & User Reviews

As AI-powered solutions such as generative AI and chatbots spread across industries, the interest in AI data services grows. One such service is a data crowdsourcing platform. Harnessing the power of a large group of people to gather data, these platforms can significantly enhance your data collection efforts, offering detailed insights quickly and efficiently.

In this article, we help you find the right 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 market presence & experience criteria

PlatformsUser Ratings
Out of 5 (Avg)*
Number of
Reviews*
Founded inData Collection
Focus**
Clickworker4.1682005
Appen4.2541996
Prolific4.7482014
Amazon Mechanical Turk4282005
Telus International4.3102005
TaskUs4.362008
Summa Linguae TechnologiesN/AN/A2011
LXTN/AN/A2014
Surge AIN/AN/AN/A
Toloka AIN/AN/A2014
Innodata IncN/AN/A1988
DataForce by TransperfectN/AN/A1992

* Based on data from B2B review platforms, including G2, Trustradius, and Capterra

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

Table 2. Comparison based on platform capabilities criteria

PlatformsData Annotation
As A Service
Mobile applicationAPI availabilityISO 27001 CertificationCode of Conduct
Clickworker
Appen
Prolific
Amazon Mechanical TurkN/A
Telus International
TaskUs
Summa Linguae Technologies
LXT
Surge AI
Toloka AI
Innodata Inc
DataForce by Transperfect

Figure 1. Crowd size comparison

A bar graph showing the crowd size comparison of all data crowdsourcing platforms. Clickworker has the largest crowd of over 4.5 million followed by DataForce, Appen, Telus International with over 1 million.

Notes for the Tables and Figure 1:

  • The companies are sorted according to the number of reviews in both tables.
  • 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.).
  • We will not be updating these tables as frequently as our product page, so you can access the most up-to-date vendor data from our data-driven list of data collection/harvesting services.
  • In Table 2, a company is assumed to follow a code of conduct if it has a code of conduct page on its website.
  • In Figure 1, Innodata Inc. and TaskUS were not included since their crowd size was smaller than 100K.
  • For Figure 1, some vendors were also excluded since their crowd size data was not found on their websites.

Criteria for selecting the right data crowdsourcing platform

An image listing the data crowdsourcing platform selection criteria discussed in this section.

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:

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

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 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:

  • A positive review regarding the reliability of Clickworker’s crowd for obtaining AI training data.1
Data crowdsourcing platform Clickworker's positive review on reliability and ease-of-use from G2.
  • Customer review regarding Clickworker’s data annotation services.2
Data crowdsourcing platform Clickworker's positive review on data annotation from G2.

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:

  • According to recent news, Appen’s performance has been declining as it loses clients and goes through financial losses.3
  • A customer review regarding Appen’s customer support, pricing, data quality, and platform.4
Data crowdsourcing platform Appen's positive and negative reviews from G2.

3. Prolific

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

Here is a list of their offerings:

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.
  • Customers identified that some of Prolific’s workers were using AI to complete their tasks.5
  • Most of the customer reviews were regarding its research data services, which indicates that AI training data is not their primary focus.6.

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

  • A customer found its data collection service to be quick, efficient, and user-friendly.7.
  • Some customers found the quality of work to be low.8.
Negative review of Amazon mechanical turk regarding the low quality of its image data collection services from G2.

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. Its data solutions include:

  • Data collection & annotation
  • Data validation and relevance
  • AI training data

Pros and cons of working with Telus International

  • While the company offers AI data solutions, it does not focus its efforts on that area. It mainly focuses on the customer experience domain.
  • Some customers found Telus International’s data annotation service slow.9

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 other TaskUs alternatives 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

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)

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 no reviews on platforms like G2 and Trustradius were found.

What are Crowdsourcing Platforms?

Crowdsourcing platforms are online platforms where businesses can outsource tasks to a large group of people, known as the crowd. These platforms provide human-generated data on demand, aiding in solving complex problems where traditional methods may fall short. They are instrumental in collecting crowdsourced data, covering various tasks, from simple surveys to more intricate human intelligence tasks.

Their role in data collection

In a world that is increasingly leaning towards AI and machine learning models, a data crowdsourcing platform plays a crucial role. These platforms aid in collecting data for building high-quality datasets, which are essential for training robust AI and machine learning algorithms. The data collected is diverse, ensuring that the AI models trained are robust and well-tested.

Transparency statement

AIMultiple serves numerous emerging tech companies, including the ones linked in this article.

Further reading

If you need help finding a vendor or have any questions, feel free to contact us:

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External resources

Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Shehmir Javaid
Shehmir Javaid is an industry analyst in AIMultiple. He has a background in logistics and supply chain technology research. He completed his MSc in logistics and operations management and Bachelor's in international business administration From Cardiff University UK.

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