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Fast Image Annotation Tool

Solve any image or video labeling task up to 10x faster and with 10x less errors.
Kili Technology makes object detection & image classification fast and simple.
Our specialized, easy-to-use labeling tools such as bounding boxes or interactive segmentation will help you create high-quality datasets with minimal effort.

They trust us
Focus on training data quality rather than quantity
Discover how Kili Technology will help you create accurate training data

[1]
Efficient Image Annotation Tool
Kili Technology’s annotation tool facilitates assigning annotations to graphical datasets in a variety of formats: from simple PNG or JPG images to more complex satellite imagery and DICOM images used for medical purposes.
Our platform is designed to create high-quality training datasets fast. All our interfaces are optimized with focus on productivity and quality and open to various types of automation: from smart tools that speed up labeling to importing full annotations created by external models.
For image classification, we cover the whole spectrum: from simple single-class tasks, through various multiple-choice options to more complex, hierarchical class arrangements that address complex ontologies.
For object detection tasks, we offer a whole host of useful tools with varying complexity: from points and polylines, through polygons and bounding boxes to more complex mechanisms like pose estimation or interactive segmentation.

[2]
Quality-Focused Image Annotation Platform
The quality of your training dataset is the main focus of our image annotation tool. Focus review on data that matters by creating an efficient communication flow between annotators and reviewers.
Iterate quickly with annotators on labels to modify & avoid drift in quality. Quantify quality with insights from advanced quality metrics. Look at labelers’ disagreements to identify misunderstandings among your annotator population.
Filter on data slices with low quality metrics. Compare quality between labelers or against a predefined standard. Boost data quality with programmatic error spotting by building automated QA scripts in the labeling interface or use external error detection models. Orchestrate all your quality strategies with automated workflows.

[3]
Integrated Image Annotation Platform
Kili Technology is designed as a solution open to others ecosystems: our Python API makes Kili Technology easily integrable into your stacks. You can natively plug in YOLO and all Hugging Face models to do transfer learning and speed up the annotation process. You can also integrate natively with your current image storage in AWS, GCP or Azure buckets.
Leverage a suite of quality image annotation data tools & services
Everything you need to label at scale and master the quality of image labels

The right image tooling

All purpose image tooling with bounding boxes, polygons, segmentation, pose estimation, etc.

All image formats supported: geospatial, satellite, traffic, medical, etc.

Advanced smart tools with interactive segmentation, and auto-annotation

Support for large images & labeling optimization with support for tiles and small objects

Auto ML & pre-labeling for productivity

Advanced data quality analytics

Powerful workflows & advanced queue management

Labelers & data quality refined analytics

Advanced filtering to spot errors

Automated QA configuration

Native data integration

Advanced automation on labeling ops

Python SDK

SOC 2 compliance

Possibility of on premise data and/or full on premise deployment

Fine-grained access rights management with predefined roles & SSO integration

The right expertise

On demand expert workforce

Full project management

World class support

ML & Data Labelling expert
What is the best image annotation tool?
Understand where your best fit is
Model assisted labelling
Interactive segmentation
Pose estimation
DICOM support
GeoTIFF support
Optimized tiling of HD images
Complex ontologies
Advanced QA analytics
Programmatic QA
Python SDK & CLI
On-premise data
Hugging Face models
SOC2
Model assisted labelling
Interactive segmentation
Pose estimation
DICOM support
GeoTIFF support
Optimized tiling of HD images
Complex ontologies
Advanced QA analytics
Programmatic QA
Python SDK & CLI
On-premise data
Hugging Face models
SOC2














Model assisted labelling
Interactive segmentation
Pose estimation
DICOM support
GeoTIFF support
Optimized tiling of HD images
Complex ontologies
Advanced QA analytics
Programmatic QA
Python SDK & CLI
On-premise data
Hugging Face models
SOC2














Model assisted labelling
Interactive segmentation
Pose estimation
DICOM support
GeoTIFF support
Optimized tiling of HD images
Complex ontologies
Advanced QA analytics
Programmatic QA
Python SDK & CLI
On-premise data
Hugging Face models
SOC2














Model assisted labelling
Interactive segmentation
Pose estimation
DICOM support
GeoTIFF support
Optimized tiling of HD images
Complex ontologies
Advanced QA analytics
Programmatic QA
Python SDK & CLI
On-premise data
Hugging Face models
SOC2














Model assisted labelling
Interactive segmentation
Pose estimation
DICOM support
GeoTIFF support
Optimized tiling of HD images
Complex ontologies
Advanced QA analytics
Programmatic QA
Python SDK & CLI
On-premise data
Hugging Face models
SOC2














Labelbox
Labelbox is a data labeling platform that enables image annotation with polygons, bounding boxes, lines, and other advanced labeling tools. It was created in 2018 and is a data and image annotation tool. It offers AI-enabled labeling tools, labeling automation, human workforce, data management, and an API for integration.
Scale AI
Scale AI is a service company that has recently developed a platform for annotating large volumes of 3D sensor, image, and video data.
Scale AI offers pre-labeling with ML models, an automated quality assurance system, dataset management, document processing, AI-assisted data annotation, generation of synthetic data and super-pixel segmentation. These services are focused on data processing for autonomous driving.
This data annotation tool supports multiple data formats and can be used for a variety of computer vision tasks, including object detection, classification, and text recognition.
V7 Labs
V7 Labs is an automated video and image annotation tool combining dataset management, image and video annotation, autoML model training to automatically complete labeling tasks and model performance analysis. The company focuses on computer vision use cases.
SuperAnnotate
SuperAnnotate is a data annotation tool for engineers and labeling teams. The platform includes a simple communication system, recognition enhancements, image status tracking, dashboards, all optimized for image annotation. Labelers can also leverage automatic predictions and data management systems.
Dataloop
Dataloop’s tools focus on automating data preparation. Their main focus is on computer vision based data labeling, but they also support annotation on audio, text, forms and
Frequent questions
