Human in the loop
Data Labeling Outsourcing Services
Accurate text, image and video labeling, done by humans, for your AI projects
DATA LABELING SERVICES
Data Annotation & Labeling: Text, Image and Video
Human-powered data labeling services tailored for companies working on AI projects. We provide scalable, affordable, and fully managed services to meet your data labeling needs, ensuring you receive precise and accurate training data.
How the Data Annotation Process Works
Handing over a critical part of your AI development might feel like a leap, but the process is simpler than you think:
You provide the raw data: Whether it’s images, text, or video, we take your data as it is.
We get to work: Our team follows your specific guidelines to label the data accurately.
Quality assurance: Each dataset undergoes thorough checks to maintain accuracy and consistency.
You receive the labeled data: Ready for immediate use in your AI model, delivered in the format you need.
No complex onboarding, no micro-management.
German efficiency & Kenyan resourcefullness
The are plenty of data labeling services out there. So why choose Bogner & Partners data annotation services in Kenya?
Expertise
We specialize in AI data annotation and understand the importance of precise data annotation.
Scalability
Whether you need 1,000 data labels or a million, we’ve got the capacity to deliver.
Speed
We know time is crucial in AI development, and we get your labeled data back fast.
Quality Assurance
Every dataset goes through multiple rounds of quality checks to ensure consistency and accuracy.
Best of Both Worlds
We’re based in Kenya and Germany with a team that bridges both Western and African work cultures, meaning you get the best of both worlds—cost-effective solutions without sacrificing quality
Image (Photo) Annotation. Annotation of images by bounding boxes, polygons, key points, or semantic segmentation masks to identify objects or regions within the image.
Data Tagging. Assigning tags or labels to data to provide context or categorization for machine learning algorithms.
Text Annotation. Annotation of text data by analyzing and classifying text into predefined categories, entity recognition, sentiment analysis, or named entity recognition.
Data Categorization. Categorizing or classifying data into specific classes or categories based on predefined criteria.
Video Annotation. Annotation of videos by adding temporal annotations, object tracking, activity recognition, or event labeling to help train algorithms.
NLP. Natural Language Processing: Annotation of text for tasks such as sentiment analysis, named entity recognition, part-of-speech tagging, or intent classification.