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We work with AI teams to understand model learning needs, design the right data, and engineer its production at scale—for the era of Physical Superintelligence.
The challenge is not simply generating more examples. It is identifying what experiences a model needs to learn from.
Our in-house AI researchers work alongside clients to uncover model capability gaps, define learning objectives, and design research-informed data solutions for the physical world.
Identify learning gaps, target capabilities, and the data signals that matter.
Shape tasks, distributions, environments, and evaluation criteria around the model.
Engineer reliable production and quality systems, with expert validation in the loop.
OPix Labs goes beyond data production to actively participate in data design. Our in-house AI researchers work alongside clients to understand model learning needs and design research-informed data solutions. Our engineers translate these designs into scalable, high-quality datasets through proprietary technologies and efficient production systems.
From procedural worlds to robotics and physical dynamics, we shape data programs around the capabilities clients are trying to teach their models.
Controllable geometry, code-to-Blender workflows, simulation-ready scenes, and structured ground truth—built around explicit learning objectives.
Research-designed video sequences and tasks covering motion, temporal structure, physical consistency, and long-horizon dynamics.
Action trajectories, demonstrations, object interaction, pose and task data for robotics and embodied intelligence—grounded in real-world expertise.
Capability-focused benchmarks, reproducible evaluations, automated quality checks, and expert feedback to measure data usefulness.
Not just more data.
Data designed to unlock the next model capability.
We work with clients to define the learning need, design the right data specification, build efficient production systems, and verify each delivery against clear criteria.
# Research with the model team
model_need: physical_reasoning
target_skills:
- object_interaction
- motion_prediction
failure_modes: to_investigate
success_metrics: jointly_defined* Illustrative production flow. Scopes, deliverables, and validation methods are tailored to each engagement.
OPix unites in-house AI researchers, engineers, and industrial experts. Research informs what data matters. Engineering makes it scalable. Industry expertise grounds it in real tasks and constraints.
Work with clients to identify model learning needs and design capability-aligned data.
THE LEARNING OBJECTIVETurn research designs into reliable pipelines, scalable production, and automated QA.
THE PRODUCTION SYSTEMBring robotics, operations, physical processes, and domain knowledge into data creation.
THE REAL-WORLD CONTEXTResearch-informed by design. Engineered for scale. Grounded in the real world.
THAT'S THE OPix DIFFERENCE.Tell us what your model needs to learn next. We'll work with you on the data design, production approach, and evaluation strategy to help close the gap.
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