Making AI Possible with Right Data and Image Annotation Services

A low-cost annotation service for machine learning and artificial intelligence companies seeking high-quality training data for diverse businesses.
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A Precise Annotation Services with Pixel Perfection

Providing the annotated image data for computer vision platforms allowing machines to detect images and classify the objects in different categorize. Anolytics makes data labeling possible for every industries to develop AI-based functional model work properly without any error.

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Get the best-in-class quality services with highest accuracy level delivering an excellence in image annotation through multiple stages of auditing and reviewing of labeled data.

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We are certified with SOC 2 TYPE 1 Company for maintaining the high standards of data security with privacy while working with our clients to ensure their confidentiality.

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Working with hundreds of workforce to annotate pictures as per the demand providing a completely scalable solution with turnaround time to meet the different client’ needs.

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Image annotation outsourcing to us means our clients get a cost-effective data labeling service helping them to minimize the cost of their project with best efficiency.

Helping 100+ Companies Achieve AI Excellence


We are providing image annotation for machine learning using the advance tools and human powered skills to make each image easily recognizable for machines or computer vision. We can label each data or annotate different types of objects like cars, human, animals or trees etc. using the various modes of annotation as per the client’s needs.


Semantic Segmentation helps to solve the vision problem in outdated computer that involves taking raw data like 2D images as an input and convert them into a mask with areas need to be highlighted. In semantic segmentation masses parts of images together belongs to the same object interested by the users and solve the computer vision problem.

Semantic segmentation
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Polygon or Polygonal segmentation will help you to annotate irregular or coarse object that are in asymmetrical shapes. It helps to capture the large images like aerial photography for more precise annotation. Annotate your images with bounding polygons with higher-level of precision to build a sharper and correct vision models for aerial imagery.


Outline the objects using bounding boxes for in depth recognition either its humans, cards or other objects on the streets. We use 2D and 3D bounding box annotation tool depending on your quantity and quality of data. We will help you train the autonomous vehicles recognize such objects with proper tagging and classification to ensure the quality.

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Polygon Annotation

Drawing precisely with contours in polygon shapes over the products to detect the objects and localization of videos or images.

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Semantic Segmentation

It is the process of image annotation by partitioning the images into multiple segments for autonomous vehicles and healthcare.

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Polylines Annotation

Applied into lane detection on roads for autonomous cars and other vehicles to detect the lane and move into the right direction.

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Bounding Box

A popular method of classifying objects in images or videos for retail, robotics, autonomous vehicles, Machine learning needs.

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Landmark Annotation

Plotting a sequence of points correctly to determine the shape of natural objects like facial features, emotions and expressions

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3D Cuboid Annotation

Capture the object in 3D cuboid to get the more in-depth dimension view and build a more comprehensive model for detailed info.


Our Image Annotation service is spread over wide-range of industries working on AI-based or machine learning-based business models. From ecommerce to retail and healthcare, we cover most of them with same level of dedication and quality.

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Self Driving

Used for computerized vision learning for autonomous vehicle driving

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Health Care

The diseases diagnosis and analysis through annotated medical imaging

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AI in Retail

Used for Ecommerce and retail supermarkets through vision based inspection

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Autonomous Flying

Mainly used for aerial view capturing and object recognition through drones

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Used as robotic arms for material handling at warehouse or assembly plants

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Mainly used to keep monitoring the objects through automated security cameras

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Satellite Imagery

Used for satellite images to get the view for urban management and smart cities

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Used as robotics in agriculture for soil monitoring, crop harvesting or yield analysis

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