Empowering AI with Human Expertise

We enable machine learning teams to supercharge their AI models through the perfect blend of technology and expert human insight

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Our customers

We collaborate with machine learning teams worldwide across industries like healthcare, manufacturing, robotics and agriculture

use cases

Data labeling for diverse AI applications such as RLHF, LLM, Semantic, Classification, Curation and more

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Looking for domain experts to train and evaluate your models?

About Us

We enable machine learning teams to supercharge their AI models through the perfect blend of technology and expert human insight.

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Featured Clients

Trusted by machine learning
teams worldwide

selected Projects

Consistently exceeding benchmarks for precision and client satisfaction

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How SUPA helped a Mobile App Design company classify mobile screen interfaces into 117 different categories

SUPA helped a mobile app design company scale their interface database 16x in 3 months with 90% accuracy, freeing resources for AI innovation.

problem

The Client needed to expand its mobile app screen and interface design database to 117 categories to train their AI model.

solution

SUPA’s highly-trained workforce and proprietary platform enabled a streamlined workflow that ensured consistent throughput while maintaining high-quality standards.

result

The Client expanded and scaled up their database by 16 times within 3 months.

greyparrot.ai

How SUPA helped a Mobile App Design company classify mobile screen interfaces into 117 different categories

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

SUPA’s strategic use of graphic design experts for generative model excellence

SUPA leveraged domain-specific talent to source and label 600k stylized vector images, solving data diversity challenges

problem

The client struggled to source and label 600,000 diverse vector images for training a stylistically versatile GenAI model, hampered by inconsistent vendor quality.

solution

SUPA rapidly scaled domain-expert graphic designers to curate, label, and sketch assets via iterative workflows and ML-aligned quality checks.

result

SUPA delivered the dataset in three months with only 3.5% rework, enabling a 37% FID score improvement in the client’s AI model for style-diverse outputs.

greyparrot.ai

SUPA’s strategic use of graphic design experts for generative model excellence

STEM Dataset

Bilingual Multimodal STEM Dataset — a curated collection of 500 Math and Physics questions in Malay and English, some enriched with relevant images.

problem

AI models often struggle with bilingual and multimodal STEM tasks due to a lack of high-quality, domain-specific datasets in languages like Malay and English.

solution

We created a curated dataset of 500 Math and Physics questions in Malay and English, complemented by a public leaderboard to benchmark AI model performance.

result

AI teams now have a reliable resource for fine-tuning and evaluating models on real-world STEM tasks, setting a new standard for bilingual and multimodal AI development.

500 high-quality Math and Physics questions

Evaluation Leaderboard

STEM-focused AI evaluation

greyparrot.ai

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

Highlights

The SUPA Advantage

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delivering data at scale

We deliver over 1 million data points every week

>95%

UNMATCHED ACCURACY & CONSISTENCY

We maintain over 95% accuracy across ongoing projects

8 years

proven expertise

We bring 8 years of proven expertise in data labeling and curation

Empowering AI with Human Expertise

Trusted by machine learningteams worldwide

Consistently exceeding benchmarks for precision and client satisfaction

How SUPA helped a Mobile App Design company classify mobile screen interfaces into 117 different categories

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

SUPA’s strategic use of graphic design experts for generative model excellence

STEM Dataset

Advancing AI Waste Intelligence

The SUPA Advantage

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Looking for domain experts to train and evaluate your models?

Trusted by machine learning
teams worldwide

Find us on
Hugging Face
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