Brodbot team has over two years of experience in working on data annotation such as 2D and 3D image labelling for autoindustry. We provide high quality solutions, at the same time respecting customers' wishes and work under their guidance (instructions) to reach the goal quickly.


Data annotation in machine learning is a process of labelling any of data.

Raw data includes:

  • Images

  • Video

  • Audio files

  • LiDAR system

  • Radar system

Data annotation is basically done by humans manually using the annotation tools or software to store the large volume of data stored after annotation.



Brodbot team, with it's experience in data annotation and computer vision, can offer our customers precise data labeling with high quality assurance.


We provide large amount of annoted data in real world scenarios. And, while labeling, we gather corner cases in order to improve the process of machine learning.


Our team can provide custom tool developement, according to customers' needs with desired output, and with our experience and corner cases we create user guidebooks for any discipline related to data annotation.


We are developing our own labeling tool for data annotation and also instructions. In the work so far we were working in customer's annotation tools or softwares.

Most commonly used technique for image annotation is bounding box (2 dimensional or 3 dimensional).

Other different types of data annotation are:

  • Polygon annotation

  • Semantic annotation

  • Line annotation

  • Tagging and descriptions

  • Optical Character Recognition (OCR)


Brodbot works turnaround time with scalable solutions and flexible image annotation pricing to give best quality annotation services primary for automotive industry.


We've already done numerous projects which makes us experts in project management able to solve potential issues. Under the guidance of professionals we guarantee confidentiality, trust and quality.


Our team is young, but experienced, we believe in the progress and together we can make things work.