Loading
Loading

Fast Image Annotation Tool

Complete any image or video labeling task up to 10x faster and with 10x fewer errors. Kili Technology makes object detection and 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.

fast-image-labeling-software

They trust us

Focus on training data quality rather than quantity

Discover how Kili Technology will help you create accurate training data

worker-herlmet-labeling-on-kili-technology-platform

[1]

Efficient image annotation software

Kili Technology facilitates assigning annotations to graphical datasets in various 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 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.

Request a demo
road-labeling-on-kili-technology-platform

[2]

Focus on quality

The quality of your training dataset is the main focus of our image labeling tool. Focus review on data that matters by creating an efficient communication flow between annotators and reviewers.

Together with your annotators, iterate quickly on labels to fix errors and boost quality. Quantify quality with insights from advanced quality metrics.

Filter on data slices with low quality metrics. Compare quality between labelers or against a predefined standard to pinpoint root causes for issues. Boost data quality with programmatic error spotting by building automated QA scripts in the labeling interface or using external error detection models. Orchestrate all your quality strategies with automated workflows.

Request a demo
integrated-image-labeling-platform

[3]

Integrated image annotation software

Kili Technology is designed as a solution open to other 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.

Request a demo

Leverage a suite of quality image annotation tools and services

Leverage a suite of quality image annotation tools and services Everything you need to label at scale and master the quality of image labels

test

The right image tooling

check mark

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

check mark

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

check mark

Advanced smart tools with interactive segmentation and auto-annotation

check mark

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

check mark

Auto ML & pre-labeling for productivity

check mark

Advanced data quality analytics

check mark

Powerful workflows & advanced queue management

check mark

Labelers & data quality refined analytics

check mark

Advanced filtering to spot errors

check mark

Automated QA configuration

check mark

Native data integration

check mark

Advanced automation on labeling ops

check mark

Python SDK

check mark

SOC 2 compliance

check mark

On-premise data and/or full on-premise deployments possible

check mark

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

test

The right expertise

check mark

On-demand expert workforce

check mark

Full project management

check mark

World-class support

check mark

ML & Data Labelling expertise

What is the best image annotation tool?

Understand what your best fit is by considering these key features:

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

check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark

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

Competitor logo
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark

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

Competitor logo
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark

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

Competitor logo
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark

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

Competitor logo
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark

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

Competitor logo
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark
check mark

Labelbox

Labelbox is a data labeling platform that enables image annotation with polygons, bboxes, lines, and other advanced annotation tools. It was created in 2018. 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 with 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 annotation services are focused on data processing for autonomous driving.

V7 Labs

V7 Labs is an automated video and image annotation tool combining dataset management, image and video data annotation, and autoML model training to complete labeling tasks and model performance analysis automatically. 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, and dashboards, all optimized for image annotation. Labelers can also leverage automatic predictions and a data management system. 

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 and forms.

FAQ

How the user interface of my data labeling software can help me obtain high quality training data?
What file formats are supported for image labeling?
To what extent is manual annotation a must for image labeling?
What are computer vision workflows?
What are the basic annotation types one can use for image labeling?
What image annotation tasks are supported by Kili Technology?
What is semi-automatic annotation interpolation?
Free image annotation vs. paid image labeling tool: who wins?
Are open-source image annotation tools worth it?
Does Kili Technology support automated annotation?
Does Kili Technology support multi-frame object tracking?
Does Kili Technology support the active learning feature?
How do you annotate an image?
Can you give me an example of an image annotation project?
What is the best neural network architecture to use for an object detection model?
What are the recent open-source implementations for image annotation?
Are there any tools or algorithms that can correct image annotation errors?
Can you list a few useful tricks to speed up image annotation?

Learn more

Get started

Get started

Get started! Build better data, now.