Overview AIsmartz delivers pixel-level accuracy at scale with annotation services such as nested object classification, pattern recognition, detection, segmentation, bounding boxes, and key point annotation, enabling quick and precise data labeling for any computer vision use case.

Our managed teams work as your team extensions with on the job experience of labeling thousands of visual and sensory datasets and providing annotation accuracy to millions of images. Our workforce solution gives you the flexibility of working on your inhouse tools or on third party platforms as per your scale of operations. We empower your in-house data scientists as they reduce their human effort on labeling and optimize time towards core machine learning operations which are critical to model success.

Our Expertise

Having worked on complex edge cases and nuanced taxonomies, experts at AIsmartz leverage their access to best in class tools due to our partnerships with leading annotation platforms. Latter ensures your access to team’s task progress, hours spent and dataset accuracy of labelled output images and videos.


Computer Vision experts outline artifacts in 2D & 3D for in-depth recognition to identify and classify objects in images and videos for machine learning processes in use cases such as retail, robotics, drone imagery, and autonomous vehicles.


Our data labeling team outlines the exact shape of the target object to annotate its precise edges effectively by drawing pixel-perfect polygons.


Generally used for detecting street lines in drivable areas for autonomous vehicle perception models requiring edge to edge labeling.


We classify and label each pixel of an image for fine-grained understanding. It enables image classification with pixel-wise annotation to localize images with intense precision. AIsmartz team segments multiple types of objects in images belonging to a single class at a pixel level.


CV experts at AIsmartz detect the object and generate a segmentation mask to classify each pixel at object level. Therefore, solving object detection and semantic segmentation together in instance segmentation.


3D point cloud annotations are best suited for accurate ground truth realization and rapid labeling of moving objects detected by LiDAR sensors in both indoor and outdoor environments. Teams at AIsmartz label point clouds in images and videos captured by multi-sensor cameras, with annotated frame-by-frame lines.


Data labeling experts at AIsmartz render a deeper understanding of the environment by tracking objects in bounding boxes as they move through a set of video frames. We specialize in object tracking and classification thereby supporting diverse use cases including surveillance, medical imaging, traffic flow analysis, and audience flow analysis.

Point of Interest Marking

CV applications with neural networks need to identify important points of interest work best with data inputs that carry coordinates of landmark points and include temporal changes and behavioral trends. We specialize in Point of Interest Marking for Geospatial Technology and landmarking for facial imagery labeling.


Our data labellers tag features within imagery data as per the client’s model requirements to equip Machine Learning modules that train itself from our labelled dataset of multiclass images and develop a model for future prediction of similar images not encountered during training.

Data Annotation Workflow

Instructions Set

You share your sample data with business rules.

Task Analysis

Our annotation experts share their opinion on workforce hours and tools required for the job

Data Labeling with Checks

Once signed up, our teams work in close contact with you for initial 8 weeks to understand edge cases

Production Grade Annotation

QA Managers monitor throughput closely with gold standards, consensus and sampling

Exported Training Data Feedback

Finished training data run by you for feedback and info on model iterations

Our Observation

Artificial Intelligence is the next go-to tool businesses would want to employ in the near future. While there is an enormous scope of its applications to streamline operations and create customer experiences, the machine learning process holds the key to AI technology use cases. Even the most advanced algorithms may not be able to infer and act upon the ground truth if the ingested data is not of appropriate annotation quality. Thus, data labeling would be the founding block to successful enterprise-grade AI solutions ahead.

Our Client's Speak

Use Cases

Autonomous Vehicles

Autonomous Vehicles have redefined the concept of mobility and are transforming the entire automotive industry … read more


AI leveraged automation is redefining retail experiences, making it more convenient to shop and manage stores for customers and retailers respectively.… read more

Medical AI

We partner with disruptive sports analytics, pharmaceutical and healthcare AI research companies to provide high-quality, secure and HIPAA-compliant data enrichment solutions… read more

Let's Connect To Get Started

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