Empowering Robotics with Human Expertise

We help robotics and physical AI teams build better models with expertly labeled data, curated datasets and human insight.

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Our customers

We collaborate with teams building AI for the physical world, from robotics and manufacturing to agriculture.

use cases

Expert data labeling for object detection, scene understanding and model evaluation.

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Building robots that need to make sense of the world? Let’s talk.

About Us

We bring technology and human expertise together to help robotics teams turn complex visual data into datasets their models can learn from.

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Featured Clients

Trusted by teams building better AI

selected Projects

Human expertise.
Better data. Real-world applications.

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medicine

Medical expertise for precise image annotation and clinical context.

industrial

Engineering insight for visual inspection and industrial AI.

design

Design expertise for visual data curation and classification.

Turning movement into structured AI training data

SUPA brought human judgment to frame-level video annotation, helping a generative AI team build consistent training data.

problem

The client needed continuous footage divided into precisely defined actions, with consistent annotations across videos.

solution

SUPA aligned reviewers through a pilot, documented ambiguous transitions and refined segmentation rules through feedback.

result

Delivered the first batch within 48 hours and established a repeatable annotation workflow.

greyparrot.ai

Turning movement into structured AI training data

Data labeling for autonomous vehicle training

Discover how SUPA's specialized data labeling services enhanced an autonomous driving company's models, achieving 95% accuracy

problem

The client needed to enhance their autonomous driving model's accuracy in interpreting vector spaces to meet safety standards and effectively navigate diverse environments.

solution

SUPA provided expert data labeling services, combining rigorous annotator training and human-machine collaboration, along with a dedicated quality control team to ensure high-quality, consistent data.

result

SUPA continues to deliver labeled data to the Client with 95% accuracy, significantly improving the client’s model predictions and meeting tight delivery timelines since 2022.

95% accuracy

Autonomous Vehicles

Computer Vision

greyparrot.ai

Data labeling for autonomous vehicle training

Advancing AI Waste Intelligence

SUPA's labeling infrastructure helped Greyparrot.ai, a global leader in AI waste intelligence, expand to 89 categories

problem

Greyparrot undertook the task of expanding its waste recognition library to encompass 89 categories, enabling a finer analysis of various waste streams.

solution

SUPA's technological infrastructure optimized the data labeling pipeline, slashing the startup time from 2-3 weeks to a mere 24 hours, all while maintaining stringent data quality standards.

result

Drawing upon SUPA's proficiency in data annotation, Greyparrot extended its waste recognition library from 49 to 89 categories; and it doesn’t stop there.

89 classes

Waste Intelligence

24-hour start-up time

greyparrot.ai

Annotation for global agritech company

SUPA scales high-quality annotation output during seasonal data surges by 170% for a global agritech company that manages over 200 million trees

problem

Aerobotics needed to handle fluctuating, large volumes of data with high-quality annotations and a 24-hour turnaround, requiring scalable and flexible workflows.

solution

SUPA’s infrastructure enabled Aerobotics to scale up to 170% in a week without building internal annotation capacity or compromising quality.

result

SUPA helped Aerobotics validate up to 200,000 tree annotations within 24 hours at 97% accuracy, ensuring year-round volume flexibility and dependable service since 2020.

200 million trees

18 countries

Agritech

Aerial Imagery

greyparrot.ai

Structural damage classification of civil structures for a global oil and gas conglomerate

SUPA's experts scaled client's data annotation, accurately annotating 12,000+ images to boost damage classification workflow.

problem

The Client required a specialised team to identify and assess damage of civil structures with a high accuracy of at least 90%.

solution

SUPA’s engineering experts collaborated closely with the Client by co-creating the annotation workflow and assembling a team of annotators experienced with engineering-related projects.

result

SUPA’s team of 25 annotators successfully delivered the annotations with a consistent >90% accuracy.

greyparrot.ai

Structural damage classification of civil structures for a global oil and gas conglomerate

Enhancing AR footwear try-on precision through high-quality segmentation

>99% accurate semantic segmentation data for ZERO10’s AR footwear try-on, enabling a precise, immersive user experience with rapid 5-week turnaround

problem

ZERO10 required enhanced precision in their footwear try-on models to deliver a more immersive and accurate AR user experience

solution

SUPA deployed its expert annotators, skilled in semantic segmentation, alongside its advanced labeling infrastructure, ensuring high-quality, scalable data annotation

result

ZERO10 successfully launched their advanced AR footwear try-on feature, powered by SUPA’s rapid delivery of segmentation datasets with >99% accuracy, enabling superior model performance and user experience

greyparrot.ai

Enhancing AR footwear try-on precision through high-quality segmentation

Highlights

The SUPA Advantage

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data at scale

Over a million data points delivered weekly to keep model development moving.

>95%

Quality You Can Build On

More than 95% annotation accuracy across ongoing projects.

10 years

Human Expertise at Work

Eight years of experience labeling and curating data for AI teams

Empowering Robotics with Human Expertise

Trusted by teams building better AI

Human expertise.
Better data. Real-world applications.

Turning movement into structured AI training data

Data labeling for autonomous vehicle training

Advancing AI Waste Intelligence

Annotation for global agritech company

Structural damage classification of civil structures for a global oil and gas conglomerate

Enhancing AR footwear try-on precision through high-quality segmentation

The SUPA Advantage

Find us on
Hugging Face
🤗

Building the next generation of robotics? Let’s talk.

Empowering Robotics with Human Expertise

Trusted by teams building better AI

Human expertise. Better data. Real-world applications.

Turning movement into structured AI training data

Data labeling for autonomous vehicle training

Advancing AI Waste Intelligence

Annotation for global agritech company

Structural damage classification of civil structures for a global oil and gas conglomerate

Enhancing AR footwear try-on precision through high-quality segmentation

The SUPA Advantage

Find us onHugging Face 🤗

Building the next generation of robotics? Let’s talk.

Human expertise.
Better data. Real-world applications.

Find us on
Hugging Face
🤗