Data Annotation Services

We offer expert services in labeling text data, which is commonly used data for AI systems. Our team categorizes text in different languages apart from English, with this, we ensure your model clearly understands different combinations of text. Additionally, our manual annotation process helps your models identify important information in large datasets.

Our data annotation process involves manually labeling texts within datasets that carry sentiments, emotions, and attitudes. This helps your model effectively process text by more than understanding it from the language point of view and identifying the sentiments hidden behind the text. This helps you communicate with your customers on a personal level, with empathy.

We annotate data, especially text datasets by tagging specific concepts under titles and search queries, which comes helpful when it comes to train your algorithm. This helps your model to easily identify key phrases which in turn improves search relevance. Similarly, we tag data that denotes human intents so that your models can understand customer intent while communicating and give relevant solutions.

It is a critical aspect of labeling data, where we annotate different aspects within visual data. We help your models identify objects within images by labeling each one of them. Our team manually labels facial features, which helps with verification and facial recognition. Additionally, we classify different images for various use cases, for instance, our team painstakingly organizes images for e-commerce product catalogs and many more.

We annotate audio data accurately, which helps your model understand diverse natural languages. With our precise manual labeling, we enable your algorithm to understand the nuances of spoken language by capturing dialects and regional demographics. We annotate audio data with the information of the speaker, including demographic and emotion, which helps your model better understand the human language.

Our video annotation service helps your AI model clearly understand video data and process it easily. We label frames – image sequences – to train your algorithm for analyzing videos which helps in efficient recognition and computer vision. Our team labels multiple objects across different frames, and activities and actions within videos which helps in dynamic scene and sport analysis, security, etc.

We categorize data and label them from multiple formats, including image, text, audio, and video, within a single dataset. We combine video, audio, and text for generating captions automatically that can be used for social media, television, and more. Our team annotates human gestures and facial expressions which comes helpful for VR models to interpret them. Our multimodal annotation also helps users to search through any means like text, audio, or image.