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Top 12 AI Data Collection Services & Companies in 2024

Top 12 AI Data Collection Services & Companies in 2024Top 12 AI Data Collection Services & Companies in 2024

Data fuels the development of tools that help make informed business decisions. However, not every business has the ability or capacity to gather data in large quantities for data-hungry projects such as developing AI models such as NLP and generative AI. This is because of the challenges of collecting relevant data. AI data collection services can help businesses overcome these challenges and fulfill their data needs. However, with so many options on the market, it can be difficult to find a suitable data partner.

In this article, we highlight the top 12 companies on the market that offer data collection as a service and compare them to provide a transparent list. We also offer vendor selection criteria and some benefits that data collection companies can offer.

Data collection companies/services comparison

In this section, we offer a comparison of the top data collection service providers identified by our market research.

Table 1. Comparison based on market presence & experience criteria

CompaniesUser Ratings
Out of 5 (Avg)*
Number of
Reviews*
Founding yearData 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

Table 2. Comparison based on platform capabilities criteria

CompaniesData 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

* Only from B2B platforms like G2, Trustradius and Capterra.

** We consider a company to be data collection-focused if it offers data collection as its key offering on its website.

Notes for the tables:

  • Transparency statement: Sponsors of this research are linked from the table above and from other parts of this article.
  • 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 offered data collection or generation services.
  • 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.

Data collection service selection criteria

Every company/project’s data needs are different; therefore, it can be difficult to select the right data collection service that fulfills your requirements. We used the following criteria to analyze the top service provider in the market. The criteria are divided into 2 categories: market presence & experience and features.

Market presence & experience

1. User ratings

The user ratings from B2B review platforms such as G2, Trustradius, and Capterra can help buyers understand the overall performance of the data collection service provider. A higher user rating from 50+ reviews can give a comprehensive understanding of the company’s performance.

2. Number of reviews

A larger number of reviews on B2B review platforms indicates the company has a large user/customer base, and you can get a better understanding of the customers’ perspective and their level of satisfaction.

3. Founded in

The age of the company helps potential customers understand the experience the service provider has in a specific field. In our experience, an older company usually offers a more refined service. However, this is not always the case since some companies can gain more expertise in a shorter period of time. Therefore, do not recommend using this criterion on its own.

Platform capabilities

4. Data annotation as a service

Data is useless to machine learning models without annotation. Therefore, it can be efficient if the company also offers data annotation as a complementary or as a side service so the data you receive is ready to be used.

5. Mobile application & API integration

It is also crucial to check what capabilities the data collection platform of the vendor offers. Do they offer a mobile application or API integration capability?

6. ISO 27001 certification

With rising cyber security threats, having effective data protection practices in place is essential. We looked for the ISO 27001 certification.

7. Code of conduct

Your business partner’s unethical practices will impact your reputation. Therefore, make sure the service provider follows fair trade and a clear code of conduct of fair practices towards workers.

8. Data types

We consider if the companies covered all data types. For instance, the required data for an automated driving system would be images of pedestrians, roads, streets, vehicles, etc. 

9. Dataset diversity

To evaluate the diversity level, we checked the size of the crowd or the number of participants in the company’s network. For instance, for a system to provide accurate output in various languages, the company should have to gather multilingual data through a global crowd. The larger the crowd, the more languages and dialects the network covers. For this, we created a separate comparison:

Figure 1. Crowd size comparison of data collection service providers

A bar graph illustrating the crowd size of the data collection services. Clickworker has the highest, followed by Appen and Telus International.

Notes for Figure 1:

  • In Figure 1, Innodata Inc. and TaskUS were not included since their crowd size was less than 100K.
  • For Figure 1, some vendors were also excluded since their crowd size data was not found on their websites.

Data collection company evaluation

This section evaluated each data collection company compared in this article based on its customer reviews. The evaluations are based on data gathered from the latest company news and customer reviews from B2B review platforms such as G2, Trustradius, and Capterra.

1. Clickworker

Clickworker is a crowdsourcing platform that breaks down large data projects into micro-tasks and distributes them to a global network to complete. It specializes in tasks such as AI data collection or generation, 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 (Multiple formats and specifications)
  • Audio and speech datasets (Multiple languages and dialects)
  • Text datasets
  • Data annotation service
  • Research/survey data collection
  • Reinforcement learning from human feedback (RLHF) services for AI development

Pros and cons of working with Clickworker:

  1. Customers find Clickworker’s AI services helpful and its crowd reliable.1
One of the data collection services Clickworker's positive review on reliability and ease-of-use from G2.
  • A customer review regarding Clickworker’s efficient data annotation services and its prices.2

2. Appen

Appen works with a crowdsourcing platform to offer various AI services. Its offerings include: 

  • Data collection & generation (image, video, text, audio, speech)
  • Data annotation
  • Data validation

Pros and cons of working with Appen:

  • Recent news has highlighted that Appen’s performance is in decline as the company loses customers and goes through financial losses.3
  • A customer review regarding Appen’s customer support, pricing, data quality, and platform.4

3. Prolific

Prolific is another data collection company that offers AI data services through a crowdsourcing model. 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:

  • AI data collection & generation
  • AI training and evaluation
  • Academic research data
  • Survey participants

Pros and cons of working with Prolific

  • Prolific does not highlight data annotation as a service on its website. This might be an issue for customers who may prefer a single provider for data collection and annotation.
  • Most of the customer reviews were regarding Prolific’s research data services, which indicates that AI data services are not its primary focus.5.

4. Amazon Mechanical Turk (MTurk)

Amazon Mechanical Turk, or MTurk, offers a crowdsourcing platform or 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:

  • AI data collection and generation
  • Data annotation and labeling
  • Market research & surveys
  • Academic research
  • Other data services

Pros and cons of working with Amazon Mechanical Turk

  • Customers also identified that most workers on MTurk’s platform are not English speakers.6
  • A customer found its data collection service to be efficient, but the quality of the data to be low.7.

Learn about Amazon Mechanical Turk alternatives here.

5. Telus International

Telus International claims to offer customer experience (CX) and digital IT solutions. Telus also offers data services through a crowdsourcing model. Its data solutions include:

  • Data collection & annotation
  • Data generation (image, audio, video, text, speech)
  • Data validation and relevance

Pros and cons of working with Telus International

  • We did not find any reviews regarding its data collection service, which indicates that the company might focus on its customer experience and data annotation services.
  • According to reviews, Telus’s network is diverse, but its service is slow.8

6. TaskUs

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

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

Pros and cons of working with TaskUS

  • The company offers data collection and annotation for all data types.
  • The crowd size is significantly smaller than other AI data services like Clickworker and Appen.
  • The company does not offer AI data collection as its primary offering since it was not mentioned first on its website. The customer reviews also suggested that its primary focus is not data collection since no reviews for data collection were found.9

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 data collection 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 & generation
  • 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 claims to focus on collecting and labeling data for Large language models (LLMS)

Pros and cons of working with Surge AI

  • The company offers RLHF and data for LLMs
  • The company does not offer visual datasets
  • There were no customer or worker reviews found on review platforms, which makes it difficult to evaluate the company’s performance from a customer’s perspective.

10. Toloka AI

Toloka AI is also a data collection company that uses a crowdsourcing model to collect and generate data for AI models. The company claims to 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. is also a data collection and generation company that offers various AI solutions through crowdsourcing. 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 over ~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. It provides services like speech and natural language processing data, image and video annotation, and more. Its data services include:

  • Data collection and generation
  • Data annotation
  • Data transcription
  • Data moderation

Pros and cons of working with DataForce

  • The company claims to have a network of over 1 million contributors, which may make its datasets more diverse.
  • However, its performance and claims can not be verified since no customer reviews were found from B2B or B2C review platforms like G2.

Why work with a data collection service provider?

This section highlights some benefits of working with a data collection service. The popularity of data collection services, online:

1. Quality assurance

Data collection service providers often have rigorous quality control measures and standards in place to ensure the accuracy and relevance of the data being collected. They employ dedicated teams of data scientists and analysts who follow stringent protocols to maintain data integrity. This high level of quality assurance can significantly improve the performance of your AI and ML models, which heavily depend on data quality for optimal outcomes.

To maintain the quality of the AI tool, it is important to continuously develop and improve it, so it continues to provide valuable insights. Working with a data collection partner can provide you with improved datasets to re-train your models whenever required.

You can also read this to learn more about data collection quality assurance.

2. Scalability and speed

Collecting and processing large amounts of data can be time-consuming and difficult to scale, especially for businesses without the necessary resources or expertise. Data collection companies can quickly scale up their operations to meet your data needs, ensuring a steady stream of well-curated data. They have the manpower, technology, and processes in place to handle large-scale data operations, allowing for faster completion of projects.

3. Expertise and specialization

Data collection service providers specialize in data-related operations and thus have a deep understanding of various data collection methodologies, data processing techniques, and compliance requirements. They are capable and equipped to handle a wide range of data types (structured, unstructured, semi-structured) and can efficiently work with various data sources. This expertise can be incredibly beneficial, especially when working with complex AI and ML projects with exclusive requirements.

4. Higher level of diversity

Some AI systems require diverse datasets to provide an accurate output. Some data collection service providers use a crowdsourcing platform for collecting data. This approach has a unique advantage in that it allows for the collection of a large volume of diverse data quickly.

Crowdsourced data can help companies access a large pool of online talent, making it a good fit for training robust and generalized AI and ML models. Moreover, the flexibility of crowdsourcing allows for the collection of data that may not be easily accessible through other methods, such as data reflecting rare events or specific regional characteristics.

Crowdsourcing is only one of the data collection methods. Check out this article to learn more about different techniques to collect data.

5. Cost-effectiveness

Working with a data collection service can be cost-effective as it helps avoid high infrastructure costs associated with data handling processes and eliminates the expenses related to hiring and training in-house data experts.

Additionally, these services offer scalable solutions that adapt to a company’s fluctuating data needs, ensuring payment only for services used. Their expertise can drive efficiency, leading to time and cost savings.

Lastly, they mitigate the risk of costly errors in data collection and processing, ensuring accuracy that leads to better AI/ML model performance. Thus, despite an upfront cost, long-term savings can make these services a cost-effective option for many businesses.

6. Additional offerings

Data collection service providers also offer extra services that a company might require, along with data collection. Services like:

  • Performing data annotation
  • Conducting online surveys or market research
  • Data transcription, etc.

FAQs for data collection services

  1. What do AI data collection services do?

    AI data collection services harness a vast contributor network to gather new or existing AI training data, enabling developers and businesses to concentrate on other AI development facets besides dataset preparation.

  2. Why are data collection services necessary?

    With regulations tightening and data access becoming more challenging, businesses and AI developers can obtain scalable and tailored datasets more efficiently by working with data collection services.

Further reading

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

Find the Right Vendors

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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