How SuperAnnotate helps AEDIT get labeled data 5x faster

Case Studies Mar 10, 2021
AEDIT Case Study

Company overview

AEDIT builds user-first technology that transforms complicated medical information into easy-to-use tools and engaging resources to empower users throughout their aesthetic journey.

Founded by a double board-certified facial plastic and reconstructive surgeon, AEDIT simplifies and safeguards the search for aesthetic solutions and qualified providers. As a single trusted source, AEDIT offers unbiased, medically verified content to educate users before connecting them with vetted, board-certified aesthetic providers. 

Our on-demand booking tool allows users to instantly schedule appointments with providers in our network.  

The problem

AEDIT needed a platform where they could perform facial and landmark detection and have direct oversight over the annotation quality and project progress. They also needed high-quality outsourced annotations. As a result, they were looking for a complete computer vision platform with great software and services.

The solution

SuperAnnotate’s end-to-end computer vision platform

SuperAnnotate was selected by AEDIT because it was the only end-to-end platform they were able to find, providing robust tooling, deep pipeline integration, and high-quality annotation services. AEDIT also wanted to automate their annotation pipeline to deliver high-quality annotations faster and turned to SuperAnnotate to boost their model accuracy and build more efficient processes. 

The results

Increased annotation quality, better model performance, and faster project delivery 

SuperAnnotate’s advanced automation features helped AEDIT automate its data training processes. 

“We have completely integrated SuperAnnotate into our MLOps pipeline,” CTO Matthew Powers said. “We are now able to automate the delivery of assets to a team that builds our training data, synchronizes that back into our system, and kicks off training jobs. The integrated collaboration tools also played a significant role in streamlining team management, which helped us build super-accurate datasets.”

In addition, AEDIT leveraged SuperAnnotate’s services marketplace to find high-end annotation services. “Using SuperAnnotate’s services marketplace was incredibly easy,” Powers said. “We ran a pilot, selected the partner we liked best, and our project was completed right away.” 

Before SuperAnnotate, AEDIT was completely reliant on separate contractors and offshore teams. “We really lacked the automation and visibility into the quality of the annotations that SuperAnnotate provides,” Powers added.

With SuperAnnotate’s software and services, automation, and quality management features, AEDIT was able to increase model accuracy by 6% and reduce the time spent on annotation from months to days.

Key outcomes

  • SuperAnnotate’s integrated automation feature helped AEDIT reduce annotation cycle time by nearly 80%, from months to days.
  • AEDIT was also able to increase model accuracy by 6%.
  • AEDIT was able to integrate their MLOps pipeline into SuperAnnotate, allowing them to automate their ML pipeline.

Tags

SuperAnnotate

The end-to-end platform to annotate, train and automate your computer vision pipeline.

Great! You've successfully subscribed.
Great! Next, complete checkout for full access.
Welcome back! You've successfully signed in.
Success! Your account is fully activated, you now have access to all content.