Generative AI labeling
with diverse human feedback

Outperform the pack with RLHF for Generative AI

Build user-centric AI with human knowledge,
intuition and learned experience

Trusted by machine learning teams worldwide

Quality Training

We teach, train and assess our annotators on a custom training platform. Quality Scorecards are calculated weekly for each annotator.

Custom Annotation Teams

Gather domain-specific data with an annotation team curated specifically for your use case. We match their experience to the level of expertise required for your use case.


Seamless data integration with your data pipeline. Integrate human feedback and user input seamlessly into your training loop for model refinement.

Diverse Workforce

Get unbiased human feedback that respects cultural nuances and preferences. We provide multilingual capabilities, with expertise in Southeast Asian languages.

Lightning-Fast Turnaround

Iterate models quickly and get closer to optimal performance before your competitors.

Built-in Feedback Loop

Fine-tune your model responses with RLHF through real-time model interactions.

Jonas Olausson
Data Engineer at
Way easier than Amazon Sagemaker and Labelbox

The best interface for self-service labeling. Everything from uploading data to seeing it labeled in real time was really cool. Very impressed with how the platform delivered exactly the label quality we needed.

Sparsh Shankar
Associate ML Engineer at Sprinklr
Incredible turnaround

The annotators were really quick. Checked 5 minutes after uploading data - 100 images done.

Sravan Bhagavatula
Director of CV at Greyscale AI
Better iterations

Real-time view of the generated labels gave me instant feedback about the label quality. No more waiting for the whole batch. This replaced my standard manual QA process using external tools like Voxel's FiftyOne.

Puneet Garg
Head of Data Science at Carousell
High quality labels

SUPA has provided us with good quality judgments to train, tune, and validate our Search & Recommendations models. Before this, it was difficult to scale our labeling workflows.

Bryce Wilson
Data Engineer at
Consistent support

What stands out is their commitment to providing consistent support throughout the data labeling process. The team actively engaged with us to clear up any ambiguity in the dataset including edge cases we didn't foresee.


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