Humanity’s future is either among the stars, or in slow retreat. We hope to add one small brick to the road outward.
GaussMathematics
We turn complex environments into model-ready data systems.
GaussMathematics builds the data layer for machines that need to understand, predict, and act in the world. We work with customer-authorized game environments, licensed virtual assets, simulations, and physical systems to produce structured multimodal datasets, action-state trajectories, evaluation sets, and customer-specific data engines. For frontier teams, the hard part is rarely collecting more files. It is turning environments, behaviors, states, and outcomes into reliable training and evaluation systems.
What we deliver.
From targeted datasets to scalable data engines.
Targeted Datasets
Dataset design, collection, annotation, cleaning, curation, and validation for specific model objectives.
Customer-Specific Data Engines
Scalable pipelines for multimodal production, QA, versioning, evaluation, and continuous data improvement.
Virtual World Data
Game data and structured captures from customer-authorized environments, licensed virtual assets, licensed 3D worlds, simulations, and interactive systems.
Embodied AI Data
Action-state trajectories, demonstrations, task states, failure recovery, and evaluation sets for robotics and physical AI.
Built for different frontier teams.
Different models need different worlds, signals, and feedback loops.
World model teams
Build post-training and evaluation data for world models with world-state structure, temporal coherence, spatial intelligence signals, and model-review loops.
Game and virtual world companies
Turn interactive environments into reusable AI training data engines while preserving control over worlds, virtual assets, permissions, and confidentiality.
Robotics and embodied AI teams
Produce action-state trajectories, demonstrations, recovery behavior, and evaluation loops for policies that must operate in the real world.
Generative video and 3D teams
Capture camera motion, scene consistency, material variation, environment dynamics, and controllable world data for generative video, spatial intelligence, and AI agents.
How we work with frontier teams.
Start with the learning objective
We begin with the capability, behavior, environment, or failure mode the model needs to learn.
Build around the environment
We design the schema, workflow, QA process, and production pipeline around the world the model must understand.
Deliver confidentially and iterate
We protect customer environments, datasets, and model goals while using feedback to improve the data program over time.
Experienced teams. Confidential delivery.
Operating across Singapore and San Francisco, with engineers from NVIDIA, Qualcomm, miHoYo, and world-class research institutions.
We are already supporting leading world-model, game, embodied AI, and robotics companies. Many engagements remain confidential by design because frontier work often involves proprietary environments, unreleased products, internal datasets, and model goals.
Pauca sed matura.
Few, but mature.
— Carl Friedrich Gauss
We prefer precise, mature data systems over generic volume.
If your model needs a deeper read on the world, we’d like to hear what you’re building.