“With the expansion to 89 classes, this granular data unlocks further digitisation and automation capabilities for recycling operations as well as provides rich data for the waste ecosystem. SUPA's labeling support has been instrumental in our accelerated progress.”
– Dominic Calina, Head of Data at Greyparrot.ai
The Problem
Recognizing waste objects accurately is pivotal in optimizing recycling processes. Greyparrot faced the challenge of enhancing its waste recognition library to provide more granular analysis of waste streams, enabling recycling facilities to improve efficiency and sustainability efforts.
The Solution
Partnering exclusively with SUPA, Greyparrot embarked on a journey to enrich its AI models with high-quality labeled data. SUPA's specialized annotators, equipped with domain knowledge, collaborated closely with Greyparrot to continuously scale classes, ensuring the accuracy and relevance of the data. Additionally, SUPA's tech infrastructure streamlined the data labeling pipeline, reducing start-up time from 2-3 weeks to just 24 hours, while upholding data quality standards.
The Results
The ongoing collaboration between Greyparrot and SUPA yielded profound results:
This exclusive partnership propelled Greyparrot to expand its waste recognition capabilities, consequently reshaping the waste recycling industry.
Let us walk you through the entire data labeling experience, from set up to export
Schedule a chat.png)
.png){kind=small}
.png){kind=small}