Mantis

Founded by Georgia Witchel in 2025

Physics-Enhanced Datasets for Low-Resource Machine Learning

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You can use Mantis to create synthetic datasets when you don't have enough real-world data for machine learning projects. It combines large language models with physics simulations to generate realistic human behavior data. This helps you build predictive models even when original data is rare or hard to access. The digital twin technology creates high-fidelity simulations that can replace scarce training data for AI applications.

What Mantis does

Generate synthetic human behavior datasetsCreate physics-based simulations for data augmentationBuild digital twins of human interactionsConvert limited data into comprehensive training setsSimulate rare behavioral patterns for model trainingCreate predictive models from scarce data sourcesGenerate synthetic data while preserving privacyCombines large language models with physics simulationsCreates digital twins of human behavior patternsGenerates synthetic data from rare datasetsConverts difficult-to-access data into predictive modelsProvides high-fidelity physics-based simulationsSpecializes in human analytics applications

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