The Annotell Annotation Platform helps you agree at scale through team-oriented workflows. Using intuitive collaboration tools we communicate the desired outcome to the annotation team.

Once you agree on what you want, you need a lot of it. Our Annotation Engine supports the process and makes it possible to create large amounts of consistent annotations in a cost efficient way. Our engine reduces the time wasted on reviewing and correcting bad annotations.

Why are we needed?

The bottleneck for most machine learning teams is lack of consistent training data.

Artificial Intelligence and machine learning applied correctly can create tremendous of value. However, many machine learning teams are constrained by their lack of consistent training data.

The hardest part of creating consistent training data is getting people to agree at scale. As machine learning systems are programmed through their training data, the training data determines the behaviour of your product.

Annotell helps your team:

• Define the expected outcome of your annotation projects and agree at scale

• Produce huge amounts of annotations consistent with your expected outcome

• Reduce time spent throughout the process

Adam Brinkman

Machine Learning Engineer, MSc

Fredrik Beiron

Software Engineer , MSc

Filip Reesalu

Full Stack Engineer, BSc

Lovisa Jäberg

UX Designer, MSc

Tina Huzenok

Quality Manager, Annotations

Jenya Luchko

Team Lead, Annotations

Hao Yang

Sales & Business Development Partner

Magnus Karlsson

Sales & Business Development Partner

Erik Wistrand

Software Advisor & Shareholder

Lennart Svensson

Science Advisor & Shareholder, PhD

Professor in Signal Processing, Chalmers

Andreas Lindholm

Science Advisor, Phd