Top 15 Data Collection Services

updated on Mar 3, 2026

Whether you need human-collected datasets, large-scale web data, or market insights, explore the options below to find the right data source for your project.

Human-collected data: AI data collection services
Web data: web data collectors
Market insights & surveys: Market research data collection services

Top 15 AI data collection services

Despite the efficiency of web data collection and synthetic data generation, human-generated data remains essential for AI development. Here, we compare the top 12 data collection services and data partners that provide human-generated datasets for AI training.

Service	Data Annotation As A Service	Mobile Application	API Availability	ISO 27001 Certification	Code of Conduct
LXT	✅	✅	✅	✅	✅
Appen	✅	✅	✅	✅	✅
Prolific	❌	❌	✅	❌	✅
Amazon Mechanical Turk	✅	❌	✅	–	❌
Telus International	✅	❌	✅	❌	❌
TaskUs	✅	❌	✅	✅	✅
DATAmundi.ai	✅	✅	✅	✅	❌
Surge AI	✅	❌	✅	✅	❌
Toloka AI	✅	✅	✅	✅	✅
Innodata Inc	✅	❌	✅	✅	❌

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

Inclusion criteria: 50+ employees and an AI data generation or collection offering.
Sorting: Vendors with links to their websites are sponsors of AIMultiple and are listed at the top. The remaining services are ranked based on their total number of reviews.
Explanation of columns: See AI data collection service selection criteria
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.).
In Table 1, a company is assumed to follow a code of conduct if it has a code of conduct page on its website.

Detailed analysis of AI data collection services

LXT

LXT is a crowdsourcing platform specializing in data collection services for AI model training and market research. The task is broken down into micro-tasks and distributed to a global network for quicker completion. So, companies can obtain large amounts of human-generated data in a shorter period of time. It specializes in tasks such as AI data collection or generation, data annotation, data categorization, and web research.

Here is a list of LXT’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

Appen

Appen offers various AI-related managed services and is a popular player in the market. However, the company is facing a significant decline in terms of customer satisfaction and finances. The company’s condition has affected its services, which has led to losing customers.

Appen provides a range of AI-related managed services and is a popular name in the market. However, the company has faced a significant decline in customer satisfaction and financial stability. This downturn has impacted its services, resulting in the loss of customers.

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

Prolific

Prolific provides a platform for generating and annotating AI training data via its community of real people. It supports multimodal data collection (text, image, audio, video) with human labeling. The company’s tasks are performed by a vetted pool of verified participants.

Here is a list of their offerings:

AI data collection & generation
AI training and evaluation
Academic research data
Online survey participants

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

Learn about Amazon Mechanical Turk alternatives here.

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

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

DATAmundi.ai

DATAmundi.ai operates through a crowdsourcing platform. Its offerings include:

Data collection for AI models
Data annotation
Data translation

Surge AI

Surge AI provides human-powered data labeling for language models, working with leading AI labs such as OpenAI and Anthropic. The platform specializes in high-quality annotation (including RLHF data).

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

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.

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.

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

Scale AI

Scale AI’s platform includes a Generative AI Data Engine that combines human-in-the-loop labeling with automated processes to rapidly create high-quality training datasets for advanced AI models. It focuses on richly annotated data for training generative AI.

The platform’s services span many industries: for example, it is used in automotive autonomy projects (with companies like GM and Toyota), and in AI systems for government and enterprise sectors.

Cogito Tech

Cogito Tech offers human-in-the-loop annotation services for LLM development, working with multimodal datasets (text, image, and audio) to support model training and fine-tuning.

The company specializes in supervised fine-tuning (SFT) and reinforcement learning (RLHF) workflows, providing expert-curated datasets to improve the performance of generative AI models.

iMerit

iMerit’s Ango Hub is an enterprise-grade human-in-the-loop data annotation platform. The company focuses on complex, regulated industries such as autonomous vehicles, healthcare, and finance/insurance. It employs a large global workforce of trained experts to annotate data at scale, supporting high-complexity AI projects.

AI 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 of top data collection services

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 of top data collection services

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 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 cybersecurity 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 whether 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 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 the data collection service providers

The Crowd represents the number of workers in the company’s network of text data collectors or generators.

Notes for Figure 1:

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

Why work with an AI data collection service provider?

This section highlights some benefits of working with an AI data collection partner. 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 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.

Market research data collection services

As the value of data increases for market research, more companies are working with data collection partners. This section lists the top data collection services for market research. Here is the comparison:

Top 6 market research data collection companies

We only selected companies with 45+ employees and market research offerings.

FAQs for data collection services

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.

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.

With the volume of data required and managed for AI projects, it can be resource-heavy to perform such tasks in-house. Working with a data collection service provider can help business leaders fulfill their data needs more efficiently.
*A data collection service can offer:
*A faster service
*Human-generated data (image, video, audio, text, etc.)
*More diverse and multilingual datasets
*Scalable services
*A cheaper option than in-house data collection.

Data collection services usually have a vast network of contributors that generate data on demand for different use cases. Some companies also offer pre-packaged datasets that have been gathered in the past.

Data crowdsourcing can benefit your business by enabling access to a large network of talent that gathers or generates fresh data on demand. Crowdsourcing platforms can provide diverse datasets that are cheaper and faster to obtain.

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