The modern AI workforce part 2: In-house or outsource?

A walkthrough on the costs, benefits, and risks of outsourcing annotation work. We also give you our recommended approach.

The modern AI workforce part 1: Why you need expert annotators

Going through the need for expert annotators and how you can minimize the cost of having expensive experts annotating for you.

The first end-to-end vision AI platform with truly automated data cleaning capabilities

Clean your data 35x cheaper using Confident Learning instead of Consensus Scoring.

The first completely free one-click segmentation tool

We are releasing a new, free feature that allows you to annotate in one-click. Read more about how it works and how you can try it here.

Opening the black box of vision AI algorithms

A pattern-matching view on convolutions and neural networks

How to nail your annotation strategy

A guide to finding the right approach for your use-case.

Levels of annotation automation

This post is a high-level exploration of the most common ways of implementing image-based deep learning (often referred to as image-based Artificial …

Advanced options

In advanced options we currently only have one option available to users. The "Automated tools generate..." toggle allows you to decide if our …

AI assistants

AI assistants are what we call our AI tooling that you can use to automate parts - or all - of your annotation work. The concept behind them is …

AI assistants status overview

Out of the many questions we get from our users, many concerns the status and training of our AI assistant models. We’re the first to admit this has …

ATOM segmenter

ATOM is a an AI-powered segmentation tool that can be used both for instance and semantic segmentation. It is available from the start of every …

Automated labelling

Automated labelling is a way for you to batch-process images in your project. Essentially, you take a model used in your project (Object Detection …