How to Choose an Annotation Outsourcing Provider: Comparing the Characteristics and Best Use Cases of Different Annotators

Are you considering outsourcing annotation but wondering, “What kind of outsourcing provider should I choose?” or “What type of annotator is right for my project?”
There are various options for outsourcing annotation, including engineers at AI vendors, part-time workers, crowdsourced workers, BPO workers, and employee annotators. Each option has its own characteristics, and the most suitable choice depends on factors such as the amount of data, project difficulty, and required quality.
In particular, for projects involving complex decision-making criteria or requiring high-quality data, “who performs the annotation” is an important consideration.

This article compares the characteristics and best use cases of different types of annotators and explains how to choose an outsourcing provider that best fits your project.

目次

1. What Options Are Available for Outsourcing Annotation?
2. Image Annotation by AI Vendor Engineers
3. Image Annotation by Part-Time Workers
4. Image Annotation by Crowdsourced Workers
5. Image Annotation by BPO Workers and Part-Time Workers
6. Image Annotation by Professional Workers and Annotation-Specialist Employees
7. Why Annotator Experience Matters for High-Difficulty Annotation
8. Why Employee Annotators Are an Option When Quality Matters
9. Yazaki's Image Annotation Service
10. Conclusion

What Options Are Available for Outsourcing Annotation?

When outsourcing annotation, there are various types of people who can perform the actual annotation work.
The most common options include AI vendor engineers, part-time workers, crowdsourced workers, BPO workers, and employee annotators.
The most suitable type of annotator depends on factors such as the amount and difficulty of the annotation work, the required quality, and the deadline.
Therefore, rather than simply asking “Which type of annotator is the best?”, it is important to compare the options from the perspective of which type of annotator is best suited to your project.

Let’s take a closer look at the characteristics and best use cases of each option.

Image Annotation by AI Vendor Engineers

When AI vendor engineers handle annotation, one key advantage is that they can leverage their knowledge of AI while performing the work.
In some cases, you can outsource not only annotation but also AI development to the same provider, making this option suitable when you want to handle AI development and annotation together.
It is also well suited to projects involving a small amount of data or agile development, where requirements are adjusted as development progresses.
On the other hand, because engineers are responsible for the annotation work, labor costs may be relatively high. In addition, since the AI development and annotation teams need to align their understanding as the project progresses, communication can also be an important consideration depending on the project.

Best Use Cases

• You want to annotate a small amount of data

• You want to outsource AI development and annotation together

• You want to adjust requirements as development progresses

• You need annotation for a project where requirements are difficult to define 

Image Annotation by Part-Time Workers

Annotation performed by part-time workers is characterized by its relatively low cost and ability to handle large volumes of data.
When part-time workers operate in the same environment as engineers responsible for AI development, they can also communicate with the engineers about the annotation requirements and proceed accordingly.
On the other hand, for projects that require in-depth knowledge of AI or annotation, education and training before starting the work are important.
When the work and decision-making criteria are clearly defined and the project does not require advanced expertise, this can be an effective way to process large volumes of data efficiently.

Best Use Cases

• You want to annotate a large amount of data

• You want to outsource relatively simple tasks

• The project does not require advanced expertise

• You want to process a large volume of work while keeping costs down

Image Annotation by Crowdsourced Workers

Annotation by crowdsourced workers is characterized by its ability to handle large volumes of data by distributing the work among many workers.
Because large volumes of annotation can be completed at a relatively low cost, this option is suitable for projects where the work is clearly defined and can be performed according to a set of rules.
On the other hand, depending on the type of annotation, workers may need knowledge of AI and an understanding of the work rules. Therefore, it is important to establish appropriate training and quality management processes in advance.
Especially for projects where workers may reach different judgments, clearly defining the annotation criteria makes it easier to maintain consistent quality.

Best Use Cases

• You want to handle a large amount of data

• You want to outsource relatively simple annotation tasks

• You want to distribute the work among many workers

• You want to perform annotation while keeping costs down

Image Annotation by BPO Workers and Part-Time Workers

Annotation performed by BPO workers and part-time workers is characterized by its ability to handle large volumes of data while maintaining consistent quality control.
By establishing work rules and quality standards in advance and having multiple workers perform annotation according to the same criteria, this option can also accommodate large-scale projects.
On the other hand, for projects requiring specialized knowledge of AI or annotation, training before starting the work and sharing clear rules are important.
This is a suitable option when you need to handle large amounts of data while maintaining a consistent level of quality.

Best Use Cases

• You want to handle a large amount of data

• You want to maintain consistent quality

• You can clearly define the work rules

• You want to outsource annotation on an ongoing basis

Image Annotation by Professional Workers and Annotation-Specialist Employees

When annotation is handled by employees who specialize in annotation, it is easier to provide worker training and quality control, while also allowing greater flexibility in responding to individual projects.
In particular, for data involving complex decision-making criteria or annotation requiring a high level of quality, the experience and skills of the annotators are important.
When annotators who understand the annotation rules continue to gain experience, they are better able to respond to the specific requirements of each project.
On the other hand, because specialized personnel are involved, costs may be higher than other options depending on the project.
This option is suitable when quality is a priority or when you need to outsource high-difficulty annotation.

Best Use Cases

• You want to prioritize annotation quality

• You need to handle data that is difficult to evaluate

• The project requires complex rules

• You want flexible support based on the requirements of each project

• You need high-difficulty annotation

Why Annotator Experience Matters for High-Difficulty Annotation

Annotation does not always simply involve identifying an object and assigning a label. Depending on the data, detailed judgment may be required.
For example, when the color of the background is similar to that of the target object, annotators need to accurately distinguish the object from the background.
In manufacturing-related data, there may also be cases where it is difficult to determine exactly what should be included in the annotation, such as the “sagging” or “twisting” of wiring.
For these types of projects, it is important for annotators to correctly understand the annotation rules and apply consistent decision-making criteria across different datasets.
Therefore, for high-difficulty annotation, it is important to consider not only the number of workers but also what kind of experience and knowledge they have.
In addition, when difficult cases arise after work has begun, having a system that allows rules to be reviewed based on questions and feedback from annotators and then reflected in subsequent annotation can help produce more consistent datasets.

Why Employee Annotators Are an Option When Quality Matters

As we have seen, each type of annotator has its own characteristics, and the most suitable option varies depending on the amount and difficulty of the data.
Especially when quality is a priority or when working with data that requires difficult judgment, one option is to have employees who specialize in annotation handle the work.
Employee annotators can more easily accumulate knowledge about annotation through continuous training and experience, while also allowing them to respond flexibly to the requirements of each project.
In addition to the annotators themselves, establishing a quality management system can also help maintain stable annotation quality.
If your goal is not simply to “process a large amount of data,” but rather to “accurately annotate data that is difficult to evaluate” or “create high-quality data,” employee annotators are an option worth considering.

Yazaki's Image Annotation Service

Yazaki provides annotation services primarily for images and video.
We support a wide range of annotation types, including image classification, object detection, segmentation, pose estimation, and 3D point clouds.
The annotation work is performed by trained employees. We provide support throughout the entire process, from requirements gathering and trials to annotation, quality inspection, and delivery.
For quality management, we have established a system with clearly defined roles for project managers, supervisors, and workers, allowing quality to be checked at multiple stages of the process.
We also support annotation for a wide range of industries and applications, including construction, automotive, real estate, disaster prevention, manufacturing, agriculture, healthcare, and food service.
If you are considering high-difficulty annotation or high-quality dataset creation, you can contact us for a free trial.

Conclusion

There are various options for outsourcing annotation, including AI vendor engineers, part-time workers, crowdsourced workers, BPO workers, and annotation-specialist employees.
Each option has its own characteristics, and the best choice depends on your needs—for example, whether you want to process a large amount of data, reduce costs, prioritize quality, or handle tasks requiring advanced judgment.
Especially for high-difficulty annotation, the experience and training of annotators can directly affect quality. Therefore, it is important to confirm “who will be responsible for the annotation.”
By selecting annotators based on the volume and difficulty of your data and the level of quality you require, you can establish an annotation process that is better suited to your project.
Yazaki provides annotation services for images and video, performed by trained employees and supported by a quality management system.
If you are considering high-quality annotation, please contact us for a free trial.