Data Annotation Management Dashboard
How to Manage Your Data
View Class Distributions of Labeling
Ensure dataset balance with expert recommendations.
Gain valuable insights through data analysis.
Improve AI model accuracy by addressing imbalances.
Image Analysis for Informed Decisions
Utilize comprehensive dataset analysis tools.
Gain insights into image resolution, dimensions, and formats.
Detect image quality, including blurry and sharp images.
Efficient Project Management through Teamwork
Assign roles with specific permissions.
Easily add team members to annotation projects.
Control annotation visibility, editing, and feedback access.
Review Your Annotations in Real-time
Easily filter and slice data based on annotation status.
Review annotated data for accuracy.
Provide feedback, and suggestions, and create issues for improved annotations.
Track, Save Time, and Analyze
Track the time saved with efficient data labeling process.
Monitor your daily labeled data and stay up-to-date on project progress.
Gain valuable insights into your data with the ability to examine class distribution.
GROW YOUR AI AND JOIN OUR
Happy Customers
Accessing high-quality and swift data is critical for an AI model to learn and adapt effectively. Co-one has enabled us to achieve this seamlessly. Their meticulous approach to collecting and processing video data, accurately annotating yoga poses using key-point data labeling, and extending data classification services, has been pivotal in training our AI model and enhancing its capability to generate personalized yoga flows. Co-one has proven to be more than just a service provider. They have been a strategic partner, contributing to the success of our AI engine and ultimately, to the wellness journey of our users.
Mehmet Uzun
Co-founder & CEO
Polyline annotation for lane detection is essential for autonomous vehicles to stay safely between lanes. The lanes on the road were labeled with high accuracy thanks to the "polylines" image annotation service provided by Co-one. Co-one's data labeling contribution helps Eatron to develop intelligent motion software efficiently.
Uğur Yavaş
Head of AI
Working with Co-one has been an extremely fast work experience. With the Intent Sentence Generation project, different sentences and unique examples were provided to our dataset in terms of content. As a result, our data set turned into a very high quality and rich content.
Fulya Terzi
Product Manager
Co-one provided intent generation and text classification to help Etiya build better-working chatbot solutions. The data labeled by Co-one as a result of the test sets (not seen by training) has given an accuracy rate of up to 91%.
Hakan Yüksel
Senior AI Manager
A fast and high quality work was carried out. It has enabled us to save staff time and therefore our costs. Since data labeling is completed at a rate that we cannot do within the company, we will be able to deliver projects to our customers in a shorter time, thus, our reputation with the customer will be positively affected.
Çağan Ekinci
CEO
The project guideline created by Co-one was explained with examples and was very understandable. The report sent to us at the end of the project was very useful in terms of the project process and numerical data. Our questions were answered immediately and solutions were produced. The process progressed very quickly. Ultimately, all our needs were met by Co-one's data solutions.
Elif Koçak
Marketing Specialist
Co-one's intent generation service for our chatbot, Maxi, has accelerated our data-feeding process by analyzing Maxi chatbot dialogs on a weekly basis, saving us valuable time and resources. Maxi's dialog accuracy rate has reached up to %98 with valuable contributions of Co-one. We are delighted with Co-one's commitment to a high data accuracy rate and look forward to continued collaboration.
Gamze Ortakaya
Innovation and Digital Strategy Sub Manager
Correct labeling in artificial intelligence models significantly affects the accuracy of the models. At Udentify, we do a lot of object detection tagging. In order to make these labels, we developed our own labeling tools and established a labeling team. Then we met Co-one and we dissolved our tagging team. Because when we saw the labels made by Co-one, we realized that we couldn’t label correctly before. The drawn boxes (bounding boxes) were complete and flawless, which greatly affects the accuracy rates. They fully complied with the predetermined labeling rules. In addition, although we do not need a lot of labeling in a very short time, we have not experienced any delays in delivering the labeling so far. Thank you Co-one team.
Sezai Acer
Director of Artificial Intelligence
Our existing deep learning model needed to be retrained with new data that the model had never seen before. The accuracy of the labels was the most important factor for us, and thanks to the strong communication of the Co-one team, we got our labels without any problems. On the other hand, being able to handle a process that would take 2 weeks in 1-2 days accelerated our work a lot. We can now get results with an accuracy rate of over 90% in examples where we could not get results before the training.
Selim Ceylan
Computer Vision Engineer
Our partnership with Co-one was transformative. They displayed exceptional professionalism in enhancing our product filtering system. From their rigorous planning and precise annotation of 8,000 products to their thorough quality assurance, Co-one exceeded our expectations. Their in-depth Dataset Analysis provided valuable insights that have since improved our platform's user experience. Thanks to Co-one, our customers now navigate our site with greater ease. We highly recommend Co-one for data annotation needs – a truly reliable and efficient partner!
Gökhan Arslan
Senior Digital Channels Growth Manager
The work was appropriate and very meticulous. In fact, it has been worked so carefully that even a contribution has been made to our wishes. We were informed at every stage of the work, the communication was very good. All our question marks about data quality have been cleared. As a result of this meticulous work, we have achieved a high quality output.
Elif Oral
Senior Data Scientist
Guide for High-Quality Annotations
Create customized annotation guidelines.
Ensure high-quality and consistent annotations.
Class-specific instructions for reliable datasets.