How to Choose the Best Data Annotation Company

Published date: 28.05.2021

Read time: 11 min

Have you ever wondered how humans identify various objects and distinguish one from another? As we grow older, we start learning new things and more information is made available to us as time goes on. One of the goals of machine learning is to teach AI systems to view the world just like a person would and replicate the human thought process. One of the most important factors in such projects is data annotation since this is what allows machines to learn from the training data. However, data annotation is a very time-consuming process which is why a lot of AI companies choose to outsource such work to a data annotation company. In this article, we will take a closer look at data annotation and tell how to choose the best service provider to perform the data annotation work. First, let’s get a definition of data annotation.

What is Data Annotation?

Data annotation is preparing the raw data used to train machine learning models with various methods that will better allow the system to “comprehend” the information. This is a very important aspect of the overall AI project because, in certain cases, a mistake could lead to disastrous consequences. For example, in areas like autonomous vehicles or medical AI there is almost no room for error because the stakes are very high. This is also why during the testing and QA processes, companies will conduct adversarial attacks on deep neural networks to make sure they cannot be tricked.

Therefore, even though data annotation is very tedious and time-consuming work, it plays a big role in creating the breakthrough in AI and ML that we read about in the news. From this we see the importance of data annotation and that the market for it is growing. But what’s behind this? We explore this question in the next section.

Why is There a Growing Need for Data Annotation Companies?

We are seeing some positive data annotation market trends. In fact, the global data annotation market is expected to see consistent growth over the next five years and be worth more than $5 billion by 2026. If we look at the US market, we see a CAGR of more than 30% from 2021 to 2027.

So what’s behind this increased demand for data annotation? One of the biggest reasons is the increased adoption of AI technology which relies on data annotation to train the machine learning algorithms that give the system to predict future outcomes and improve decision-making. Technologies self-driving cars, various robotics in the healthcare and agriculture industries as well as in many other verticals are attracting increased investments which drive the demand for AI and therefore data annotation as well.

We already mentioned earlier that businesses choose to outsource data annotation work to dedicated service providers, but such companies need to deal with certain difficulties as well. Let’s explore these next.

Common Challenges of Setting Up a Data Annotation Unit

Setting up a data annotation unit requires hiring experienced professionals to implement the project, then you need people who can set up and monitor the quality of the annotation work and let’s not forget about actually hiring the data annotators themselves. All of this requires significant financial investment and not many companies are willing to invest the needed resources into their data annotation unit. In addition to this, they need to source and recruit candidates which is a time-consuming process as well and if they are not careful and allow this process to drag on, this could delay the entire project. The best data annotation companies have all of these processes planned out and streamlined so the annotators can get to work faster.

Why is Data Annotation Outsourcing Better than Doing This Work In-House?

There are many reasons why outsourcing data annotation is the best way to go. Here are some of the main ones:

Lower costs – Not only is the cost of labor less overseas, but you also do not have to worry about overhead costs like renting office space, procuring equipment, and many other costs.
Experienced Project Management – Making sure that all of the work gets done without any delays requires a lot of knowledge and expertise. An experienced service provider will be able to monitor all of the processes and make the needed adjustments to improve workflows.
Access to a Larger Talent Pool – When you outsource your data annotation work, you get access to the best quality candidates that location has to offer. Many countries in the US and the EU like to outsource to Ukraine because of the high quality and work ethic of their employees.

There are many stable companies on the market, like Mindy Support, but how do you go about navigating all of the companies that are offering seemingly identical services?

How to Choose the Best Data Annotation Company?

There are certain qualities that set the best data annotation companies apart from the rest of the playing field. These include:

Expertise – When looking at a company’s expertise, you need to make sure that they will be able to do the job right the first time. If you think they will need several iterations to do so, then move on. Try looking at the QA processes they have in place to give an idea of how they go about data annotation. Learn more about how we manage the quality of data annotation projects at Mindy Support.
Scalability – Your project might require more data to be annotated than you originally expected. This is why you need to be confident that the service provider can scale up, without sacrificing the quality. Scalability also includes having complete control over the size of your team. Just like there might be a need to scale up, you might also want to scale down. This is why it is important that the service provider gives you such control and does not lock you into a contract.

Mindy Support recently worked on a data annotation project for the automotive industry where we needed to assemble a large team within a short period of time. The project involved working with image sequences to detect movement and direction of the vehicle. We also identified lights statuses and parking slots. We’ve annotated more than 545 million image sequences. 750 annotators were trained for the task.

Speed – You may require that a certain amount of data needs to be annotated within a particular time frame. While everybody wants their data to be annotated as soon as possible, it is important to sit down with each potential service provider to find out what it is possible to get accomplished within the time period that you require. If they give you a suspiciously short amount of time to annotate all of the data, be sure to ask them about the quality control measures that are in place.

What Else Do You Need to Look For When Evaluating Service Providers?

There are certain things you need to look for when evaluating offers from several companies:

Security – A lot of companies are hesitant to outsource their data annotation due to the sensitive nature of their project. When evaluating a given company’s security measures and practices, be sure to ask them if they have any international certifications or accreditations such as ISO 2700. This is an internationally recognized certification that is awarded only after an independent audit of the IT system to make sure that the company is in compliance with international security standards. Additional things to look for include EU GDPR compliance, and anything else they might have.

Check the list of the main security regulations to look for in the outsourcing data annotation provider.

Free Test – The service provider will usually allow you to annotate a small dataset to give you an idea of their work quality and their processes. After completing a test data annotation project, you will be able to determine if the accuracy of annotation meets your needs.
Offer a Clear Understanding of the Requirements – There will be situations where the data annotators will need to have a specific background or education. This is especially true for medical data annotation projects and the healthcare industry, where often companies require people with a certain medical degree and working experience.
Detailed Project Overview – There are many factors that will go into the data annotation project costs. This includes things like the type of data that needs to be annotated, specific techniques involved, the tools that will be used (open source or paid), etc.
Deadlines – A lot of times companies need large amounts of data annotated within a short time period. The service provider must be able to tell you whether or not they will be able to meet those deadlines. Usually bid data annotation companies have over several thousands of people in place.

Why Choose Mindy Support as Your Data Annotation Partner

Mindy Support is proud to be the largest BPO provider in Eastern Europe with more than 2,000 employees and 6 locations around the country. Our size and location allow us to assemble even the largest of teams quickly without sacrificing the quality of the data annotation. You will have complete control over the size of your team and can scale up or down wherever you would like. Learn more about our data annotation services.