Automated quality assessments at last

Encord offers the most intelligent data evaluation features, ensuring that your labels are of the highest possible quality before they go into production.

Manual computer vision quality control

The problem with existing methods of quality control

Human supervision can be highly unreliable, biased, and redundant. It also adds severe constraints on throughput where high expertise is necessary.

Non-scalable

Current rates of data growth means that we will rapidly run out people to review data.

    Biased

    Human perspectives differ, which can create disagreements on what is ground truth.

      Redundant

      Humans may be reviewing data that might not be value-add to your model.



        Automated computer vision quality control

        Augment quality control with automation

        Encord's novel quality assessment tool helps scale your quality control processes by spotting hidden errors in your training dataset.

        Fast

        Let algorithms do the grunt work - deploy humans only when necessary

        Simple

        Easy to use interface allows you to assess multiple label types.

        Transparent

        Finally a tool that helps you discover and visualise errant labels.
        Quality report workflow


        How it works

        A new approach to quality

        Encord has developed the first truly automated quality assessment tool - powered by micro-models. Instantly discover errors in your labels and make the most of human review.

        Features 01

        Model validation

        Import model predictions through our APIs and SDK to find errors and biases in your model.

        Features 02

        Predict label quality

        Use our automated quality control features to ensure only the best ground truth is delivered to your models.

        Features 01

        Expert review

        Encord supports purpose-built workflows for domain experts to drive specialised quality control.




        Get started today