Annotation
Services

Keymakr provides accurate AI training datasets for enterprises in different industries. Our in-house teams and studios enable us to offer data creation, generation, and annotation services for projects of any scope and complexity.

High-Quality Datasets
for Your Models

Our proprietary platform Keylabs.ai and professional in-house annotation team made us a leading annotation service provider on the market. Over the years, we developed a robust network of partners and sources for collecting data, opened studios around the world to create data from scratch, and set up generative AI models to offer synthetic data for fast ML training.

01. Image Annotation

We employ professional in-house annotators who specialize in different industries, and then provide them with advanced tools to perform high-quality labeling. Our staff includes medical experts, agronomists, engineers, and other domain experts to meet the needs of different projects.

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02. Video Annotation

Our platform supports complex tasks such as object tracking on multiple videos and attribute hierarchy. We process videos of any size by using bounding boxes, points, lines, polygons, and multi-segment lines to mark up video frames. Moreover, we quickly adapt and scale teams to match any annotation workload.

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03. Data Collection

We employ a wide variety of techniques to collect useful, unique, and most importantly, compliant data for your training. Our robust network of partners allows us to meet even complex requirements in highly regulated industries such as medical, waste management, manufacturing, and others.

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04. Data Creation

We have studios across the world and access to specialized equipment, including software licenses and hardware from cameras to niche recording tools. In addition, we can work with your tools and use your premises or products for unique needs in automotive, manufacturing, robotics, and other projects.

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05. Data Validation

We help increase the accuracy of your AI training datasets by verifying information in them and using human-in-the-loop techniques to improve your efficiency. In addition, our in-house team and strict protocols ensure that all your data remains safe and never gets transferred to third parties.

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06. Semantic Segmentation

We use our proprietary annotation platform to ensure pixel-perfect annotation of your images and videos. Segmentation helps your computer vision systems understand nuance and get to the next level.

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07. Automatic Annotation

We use ML models to help automatically label data, significantly increasing speed and efficiency. Our 4 levels of human-led QA and custom sanity scripts ensure that all automatically annotated data is accurate and matches the standards required for the optimal performance of your models.

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08. 3D Point Cloud

We work with LiDAR data to teach your AI models about spatial relationships between objects in the real world. This is especially important for the automotive, logistics, and aerospace industries, where autonomous navigation is enabled by Point Cloud datasets.

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09. Image Segmentation

This process ensures that every pixel in your image is accounted for, so your AI can understand full scenes rather than just fragments. We use advanced proprietary tools to achieve fast and accurate segmentation for image datasets of any size.

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10. Generative AI

We create pre-labeled synthetic data with the help of generative AI models. This helps create images or even videos in bulk, increasing the speed of training. However, the process requires strict human supervision and quality control as generative AI models are still being refined for this process.

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11. Annotation Platform

We developed a proprietary annotation platform named Keylabs.ai for enterprise-grade labeling projects. It supports every technique from bounding boxes to key points, skeletal labeling, and even 3D point cloud datasets. Our experts work with Keylabs to deliver clean and precise datasets at scale.

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Image & Video Annotation

Our annotations can have different precision levels up to "pixel perfect." All projects are managed by machine learning experts who understand exactly how your data should be labeled for training. As a result, we offer high-quality and consistent data for the optimal performance of your ML models.

Bounding Boxes

The most common annotation type that works for object recognition and tracking. It’s generally used in computer vision systems for simple tags.

Rotated Bounding Boxes

A bounding box variation placed at an angle to help your model more accurately understand the exact position of the object it needs to process.

Cuboid

This method helps extrapolate 3D objects from 2D images and videos by adding depth and height to the image for approximate dimensions.

Polygon

Helps precisely define non-standard objects by tracing their shape with small connected lines that define them. Used for added accuracy.

Semantic Segmentation

Everything in an image gets classified separately with colors assigned to objects. Helps your model process full scenes with pixel-perfect accuracy.

Skeletal

Connected lines are attached to limbs of usually humans and animals to precisely mark their position and track poses and shapes.

Key Points

Individual points are marked and assigned separate labels for specific features such as understanding human faces or emotions.

Lane

Linear structures such as roads, pipelines, railroad tracks, and other parts of the infrastructure get marked with lanes for easier processing.

Instance Segmentation

Further classification of scenes that includes assigning separate labels and colors to individual instances of each object. Highlights properties and adds precision to the data.

Bitmask

Used to accurately mark separate parts of an object as belonging to a single entity - such as a field split into two separated by something else in the foreground.

3D Point Cloud

Often used for LiDAR data in autonomous vehicles, this method helps recreate entire scenes with real-world relationships between objects in 3-dimensional space.

Automatic Annotation

ML algorithms help automatically detect objects and tag them. This method requires human supervision and QA, as well as specialized tools such as those offered by Keylabs.

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Reviews
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"Delivering Quality and Excellence"

The upside of working with Keymakr is their strategy to annotations. You are given a sample of work to correct before they begin on the big batches. This saves all parties time and...

AnnotationServices

Annotation
Services