SUPA provides high-quality training data for machine learning and artificial intelligence through a proprietary platform that utilizes a crowdsourced workforce for diverse human feedback. The company addresses the challenge of obtaining accurate and culturally nuanced data for model training by delivering over one million data points weekly, tailored to specific use cases.
Funding
Funding not disclosed
Founders
Product
Problem
Machine learning models require large amounts of labeled data for training, but obtaining accurate and culturally nuanced data can be a significant challenge, especially for generative AI and large language models (LLMs). Traditional data labeling methods often lack the speed and scalability needed to keep pace with rapidly evolving AI applications.
Solution
SUPA provides a platform and crowdsourced workforce for generating high-quality training data tailored for machine learning and AI applications. The platform focuses on delivering diverse human feedback, with expertise in Southeast Asian languages, to ensure unbiased and culturally relevant data. SUPA offers custom annotation teams matched to specific use cases, along with a built-in feedback loop for real-time model refinement using Reinforcement Learning from Human Feedback (RLHF). The platform supports various solutions, including image generative AI, LLMs, moderation, and computer vision, providing seamless data integration with existing data pipelines through an API-ready system.
Target Audience
SUPA's primary customers are machine learning teams and AI developers worldwide who require high-quality, culturally nuanced training data for generative AI, LLMs, and other AI applications.
Features
- Custom annotation teams curated for specific use cases, ensuring domain-specific expertise.
- Quality Scorecards calculated weekly for each annotator to maintain high standards.
- API-ready integration for seamless data pipeline integration and model refinement.
- Diverse workforce providing unbiased human feedback with multilingual capabilities.
- Lightning-fast turnaround for quick model iteration and performance optimization.
- Built-in feedback loop for fine-tuning model responses with RLHF through real-time model interactions.
- Support for image generative AI, LLMs, moderation (image, video, text), and computer vision (object detection, model validation, classification).
- AI Assistant to help with data labeling tasks.