Setting up a Dedicated Data Annotation Team in Ukraine: Why You Should Do It

Data annotation involves coding, labeling and structuring data of different types so that machine learning and AI algorithms can better understand and process the data. It is important that the different data types like text, images, video and audio be tagged accurately or the machine learning and AI models will perform poorly. This requires a data annotation specialist to manually tag data which is a time-consuming process due to the sheer volume of data and the need for strict attention to detail.

There are companies that prefer to do data collection and labeling in-house but there is another option. You can outsource your annotation needs to a data rating & labeling contractor, with Ukraine being one of the more popular destinations for data annotation outsourcing. Here are some of the reasons for setting up a dedicated data annotation team in Ukraine.

  • High-quality data sets: the success of AI and machine learning projects can hinge upon the quality of the data sets used. A dedicated annotation team in Ukraine will use experienced and expert data manual labeling specialists to ensure you receive data sets that are accurate and of the highest quality. An experienced team focused only on AI training data annotation will produce far better results than in-house staff that have additional duties. Team members will be familiar with different data labeling tools and have experience in diverse industries which will contribute to the success of your project.
  • Scalable: to be successful AI and machine learning projects may require anywhere from thousands to millions of labeled training items. Companies sometimes find that more data sets are required to improve results. A remote dedicated team for data labeling in AI can be quickly scaled up with skilled and experienced staff to handle increased volumes. 
  • Faster: a dedicated remote team in Ukraine will be able to complete ML data annotation tasks in less time than they can be done in-house. A data labeling specialist who is experienced and familiar with the tools will naturally be faster than newly trained in-house teams.
  • Secure: although some companies are concerned with security and data privacy issues this won’t be a problem with a reputable data labeling contractor from Ukraine. They are amendable to signing non-disclosure agreements and in addition make use of a variety of data anonymization tools to meet GDPR compliance and keep data private.
  • Less expensive: the cost of data labeling for machine learning will be lower using a dedicated annotation team from Ukraine. You won’t have to deal with recruiting and training costs and salaries in Ukraine are less than those in most Western European and North American countries. In addition associated costs like office space and equipment are eliminated when you go through a data labeling agency.

Types of Data Your Data Labeling Contractor Can Label 

Machine learning and AI projects deal with a number of different data types. The following are the different types of data the annotation specialists we hire can label for clients.

data collection and labeling

Text Annotation

Natural language processing (NLP) is one of the biggest fields of AI development and it is in part text annotation that makes NLP technologies possible. Text can be annotated in a number of different ways including text classification (document classification, sentiment annotation, product categorization), entity linking, entity annotation (named entity recognition, key-phrase tagging, part-of-speech tagging), linguistic annotation (part-of-speech tagging, discourse annotation, semantic annotation, phonetic annotation) and sentiment annotation. Machine learning text recognition using optical character recognition is another area we can assist with.

Audio Labeling

Audio annotation is used to help develop applications like chatbots and speech recognition. Tasks our audio labeling specialists can perform include speech to text transcription, audio classification and sound labeling to separate and identify different types of sounds on a recording. Services for event tracking and multi-labeling for overlapping sounds are also available.

Video Annotation

Video annotation is used to make the moving objects in a video recognizable to machine learning and AI algorithms. Every frame in a video has to be annotated and the number of frames can range from 24 to 60 frames for each 1 second of video making labeling even short videos very time-consuming. Polygons, lines and splines, 2D bounding boxes, 3D cuboid boxes and landmarks are a few of the video annotation techniques our video labelers have experience with. 

Image Labeling

The image processing services provided by our specialists involve labeling pictures for AI image recognition. There are different image annotation techniques our specialists can use depending on your requirements including polygon annotation, semantic segmentation, landmark, tagging, 2D bounding box, 3D cuboid and image masking. Image categorization is another task they can perform which is the labeling of images into different predefined categories. 

3D Point Cloud Annotation

Point clouds are 3D visualizations made up of anywhere from thousands to millions of geo-referenced points. 3D point cloud processing specialists use several annotation techniques for labeling point clouds. Objects are detected using 3D boxes, and labeling is used to match 3D point cloud data to corresponding photo images. Semantic segmentation assigns a class for each 3D point. An exceptional level of precision is achieved with 3D point annotation

Your Data Labeling Specialist Can Provide All of These Services and More

The methods used to label AI and machine learning training data will depend on the specific requirements of your project. Here are some of the data annotation services labeling professionals we hire can provide.

data annotation services

2D Bounding Box Annotation

With 2D bounding box annotation a rectangle is drawn around the object to be identified and is typically used to detect and recognize different classes of objects. This technique is applied to both images and videos and used in a wide range of industries that include insurance, e-commerce, retail, medical, robotics, security and others. It requires less time and isn’t as expensive as other methods 

3D Cuboid Annotation

3D cuboid annotation is similar to 2D bounding box but adds an extra axis providing additional information such as the height, length, width and rotation of objects making it useful for training models for spatial perception. Using cuboid annotation creates 3D models out of 2D images making it possible for models to detect and identify objects as well as recognize their placement in three-dimensional space.

Landmark Annotation

Also known as key point annotation, this technique works by placing key points across an image so that different objects within the image can be labeled. Labeling small individual objects using a single key point is one use. Another is using multiple points to outline specific details of an object such as with facial landmark annotation which uses numerous points to distinguish details and shapes of faces.

Polygon Segmentation Annotation

This technique provides more accuracy than the box and cuboid methods and is useful for labeling irregularly shaped objects. By using masks for segmentation Polygon annotation allows more precise labeling of images. Because the outline of objects is closely followed there is less noise than with 2D and 3D boxes

Semantic Segmentation

With semantic segmentation, every pixel in an image is assigned a class. The class label could be a car, a flower, a person or anything else and all objects of the same class are treated as a single entity rather than as separate instances. This is a very precise annotation method as every pixel is assigned to one class. Accuracy and consistency are improved when semantic segmentation is used.

Polyline Annotation

When it is necessary to track a shape that doesn’t start and end at the same point, polyline annotation is a good choice. It uses lines to trace the shapes of structures such as roads and railroad tracks and is most commonly used for lane detection in autonomous vehicles.

Additional Data Labeling Services

Other services our annotation specialists can provide include video event tracking to follow occurrences of interest over a period of time, image masking and data tagging for sorting and organizing images efficiently.

hire remote data annotation specialist

Industries Annotation Experts We Can Hire Serve in

Machine learning and artificial intelligence are finding their way into almost every industry imaginable. The industries the annotation specialists we hire serve include but are not limited to:

  • eCommerce and retail
  • Healthcare
  • Agriculture
  • Automotive
  • Robotics and industrial automation, 
  • Augmented Reality
  • Insurance
  • Aviation
  • Information technology
  • Manufacturing
  • Travel and hospitality
  • Telecommunications
  • Logistics and transportation
  • Banking and financial services
  • Security

Why Consider Ukraine as a Destination for Building Data Annotation Teams

Ukraine is well known for IT outsourcing but it is also an attractive destination for building data annotation teams. The following are some of the reasons for outsourcing data annotation to Ukraine:

  • Large talent pool: Ukraine has a well educated population with a large number of professionals who hold degrees from one of the many colleges and Universities in the country. They are known for IT and engineering but have professionals in many other fields as well.
  • Culture: in Ukraine the work culture is similar to that in much of Europe and North America. Finding employees who are a good fit for your business is relatively easy as they have the same work values.
  • Good location: the time difference between Ukraine and most of Western Europe is only one hour, and their regular working hours also overlap with parts of North America so scheduling meetings and contacting your team isn’t difficult.
  • Multiple languages: most Ukrainian professionals are fluent in English and many are proficient in several other languages as well.
  • Lower costs: salaries are lower in Ukraine than in North America and Western Europe for equivalent skill and experience level.

Why Choose Us for Your Annotation Needs

We are a Ukraine-based data labeling service that provides annotation specialists for a wide range of projects. Our company assists clients from diverse industries with getting high-quality data sets to train their AI and machine learning models. Some of the reasons for choosing us to provide your annotation needs include:

  • Skilled data annotation specialists: we have access to a large talent pool of professional data annotation experts with experience in many different industries.  Every data labeler we hire has been screened to verify their qualifications. High quality and accurate data sets are assured when you use our specialists.
  • We know the market: we know how to find data annotation teams that are tailored to fit your needs. Every company is different and so are their requirements. Our teams can also be easily adapted to fit your needs should your requirements change in the future.
  • Experienced outworker: the salaries of our annotation specialists are very low when you consider the vast experience that most have. Many have worked exclusively in the outsourcing market for many years.
  • Transparency: we believe in transparency when dealing with our clients. There are no hidden costs or expenses and we provide regular updates on turnaround times and quality metrics 

We offer other BPO services in addition to data labeling such as customer support teams and PEO services.

The process we use for hiring a data annotator for a dedicated team is simple but effective and consists of the following basic steps:

  1. Provide us with your requirements: we talk to you via Skype or telephone to determine the specific annotation requirements of your AI or machine learning project.
  2. Candidate selection: the resumes of the most suitable data annotation specialists matching your requirements will be sent to you for your review.
  3. Hold interviews: you conduct interviews of your preferred candidates by Skype or video conference. If you like you may administer a test to assist you in your decision.
  4. Final preparations: we establish a workflow and determine a starting date. Once the service agreement is signed everything is ready to go.

For high quality data sets to train your machine learning and AI models contact us to hire a dedicated data annotation specialist!