Train your software with precise and powerful  training data for AI.

Automated Data annotation with highly trained expert annotators for complex and intricate annotations.
At TagX, we specialize in Automated Data Annotation with Human feedback loops.

Bid farewell to the hassle of juggling multiple annotation platforms. At TagX, we offer a comprehensive, one-stop solution for all your data annotation needs. Our end-to-end services encompass creating tailored annotation guidelines, curating the most suitable foundational models, and seamlessly integrating labeling workflows – all under one roof.

Consolidate resources, eliminate platform redundancies, and leverage our efficient processes, TagX empowers you to realize substantial cost savings. Moreover, our optimized approach significantly reduces project timelines, enabling you to swiftly operationalize your data-driven initiatives and gain a competitive edge.

Want to launch that AI enabled product faster?

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Scalable and secure source for Data Annotation for AI & ML that can curate, build, and scale your vision in the most efficient way.


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Annotations Processed

TagX offers comprehensive data annotation services for computer vision projects, including image and video annotation for a variety of use cases. Our team of skilled annotators can accurately label and tag visual data to help train and develop computer vision models.

Our annotation services ensure the highest level of precision and consistency for the data labeling process, making sure that the labeled data is of the highest quality. With our services, you can be confident that the data used for training your computer vision models are of the highest quality, which in turn will lead to more accurate and effective models.

Data Annotation for Computer Vision

Image Annotation

Image annotation is the process of labeling and tagging images to provide relevant information for computer vision and machine learning models. This can include identifying objects, people, or features within an image, and providing metadata such as location or attributes.

TagX provides image annotation services for various use cases, such as object detection. Our team of skilled annotators can accurately identify and label objects within an image, providing the necessary information for training models to detect those objects in new images. We use a combination of manual and automated techniques to ensure the highest level of precision and consistency in the annotation process.

We can also perform image annotation for other use cases such as image classification, semantic segmentation, and more. Our annotation services are flexible and can be tailored to meet the specific requirements of your project. By using our services, you can be confident of receiving high-quality, annotated images that will improve the performance of your computer vision and machine learning models.

Video Annotation

Video annotation is typically performed by labeling each frame of the video individually. This process is done by manually reviewing each frame of the video and labeling the objects, actions, or features that are present in the frame. This can be done using tools such as bounding boxes, key frames, and point clouds. The annotated data is then exported in a format that can be used for training machine learning models.

Video annotation is used in a variety of applications such as Autonomous driving where we need to label objects, pedestrians, and other vehicles, in Surveillance systems to recognize objects, people, and actions in surveillance footage, in Retail to detect products on store shelves, enabling autonomous checkout, sports analysis, and behavioral analysis.

Natural Language Processing (NLP) deals with the interaction between human language and computers. TagX provides data annotation for text and audio which is crucial for NLP as it provides the training data for the models. Text annotation involves labeling and tagging text data, such as identifying entities, sentiment, and intent. Audio annotation, on the other hand, involves labeling and tagging audio data, such as transcribing speech and identifying speakers.

Labeled data by TagX is used to train models for different NLP use cases such as machine translation, sentiment analysis, speech recognition, and language understanding. For example, in sentiment analysis, text data is labeled with the positive, negative, or neutral sentiment, and this labeled data is used to train a model to classify text as positive, negative, or neutral. Similarly, in speech recognition, audio data is labeled with transcriptions of the speech, and this labeled data is used to train a model to transcribe audio data.

Data Annotation for Natural Language Processing

Text Annotation

Text annotation is the machine learning process of assigning meaning to blocks of text: whether they are short phrases, longer sentences, or full paragraphs. This is done by providing AI models with additional information in the form of definitions, meaning, and intent to supplement the text as written. TagX provides text annotation services to help NLP and AI applications by accurately labeling and tagging text data.

Our team of skilled annotators can label text data with the necessary information for training models in a variety of NLP and AI use cases, such as sentiment analysis, language understanding, and information extraction. TagX supports all types of text annotation like Named entity recognition (NER), Sentiment analysis, Part-of-speech tagging (POS), classification, and summarization. By using TagX text annotation services, you can be confident of receiving high-quality, annotated text data that will improve the performance of your NLP and AI models.

Audio Annotation

Audio annotation is used to train models to understand the intent behind the speech, which is important for tasks such as voice commands and virtual assistants. Speech recognition models use audio annotation to transcribe speech in the audio data, which helps in recognizing and transcribing speech in real-world scenarios.

TagX provides audio annotation services for various types of NLP and AI use cases, such as speech recognition and language understanding. Audio Annotation can include transcribing speech, identifying speakers, and labeling audio events or actions. Our team of skilled annotators can accurately transcribe speech and identify speakers in audio data, providing the necessary information for training models in these use cases.

How it works?

TagX provides comprehensive data services that support every step of the Machine Learning (ML) and Artificial Intelligence (AI) data pipeline. We understand that data is the foundation of any successful ML or AI project and therefore, we work closely with our clients to provide services that cover the entire data pipeline.

Data collection

TagX gathers data from various sources such as internal systems, external APIs, and public data sets. We also provide web scraping services to extract relevant data from the web.

Data Curation

Data is curated and cleaned ensuring its relevance to the project. Preprocessing is also done extract features and engineering to make the data usable for Machine Learning and Artificial Intelligence.

Data Annotation

TagX provides annotation services at scale to label the data and make it usable for training ML/AI models. We have a team of experts who are well-versed in various annotation techniques such as image annotation, text annotation, and video annotation.

Data Management

Data is very accessible and ready for analysis. We follow best industry practices to ensure data is well organized and protected. With our services, you can be sure that your data is of the highest quality and ready for analysis, allowing you to gain valuable insights and make informed decisions.

Industries we have worked with




Retail & Ecommerce


Banking and Finance


Sports & Fitness

Security & Surveillance

Real Estate

Intelligent Document Processing

Conversational AI

Logistics & Supply Chain

Warehousing & Inventory Management



Augmented Reality

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