RESEARCH-DRIVEN DATA DESIGN RESEARCH × ENGINEERING × INDUSTRIAL EXPERTISE DATA FOR PHYSICAL SUPERINTELLIGENCE
OPIX LABS / DATA DESIGN + PRODUCTION ✳

We don't just produce the data AI learns from. We help design what it needs to learn from.

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.

✳ RESEARCH-INFORMED DATA DESIGN
ENGINEERED FOR MODEL LEARNING
[01 / OUR APPROACH]DATA STARTS WITH A LEARNING OBJECTIVE

Better data
starts with
better design✳

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.

OUR DESIGN PRINCIPLEFROM MODEL NEEDS TO MEASURABLE LEARNING
A /

Understand

Identify learning gaps, target capabilities, and the data signals that matter.

B /

Design

Shape tasks, distributions, environments, and evaluation criteria around the model.

C /

Scale

Engineer reliable production and quality systems, with expert validation in the loop.

[ THE OPIX DIFFERENCE ]BEYOND DATA PRODUCTION

A partner in data design.
Not just data supply.

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.

01 / DISCOVERModel learning needsResearch with the client
02 / DESIGNData specificationsCapability-aligned by design
03 / ENGINEERScalable productionSystems, domain expertise & QA
04 / VALIDATEModel-ready dataGround truth & measurable quality
[02 / DATA SOLUTIONS]DATA ENGINEERED AROUND LEARNING NEEDS

Designed for
what comes next.

From procedural worlds to robotics and physical dynamics, we shape data programs around the capabilities clients are trying to teach their models.

01 / DATA PROGRAM↗
GEOMETRY / GENERATION

Procedural 3D
& synthetic worlds

Controllable geometry, code-to-Blender workflows, simulation-ready scenes, and structured ground truth—built around explicit learning objectives.

3D ASSETSBLENDERSIMULATION
02 / DATA PROGRAM↗
VISION / DYNAMICS

Video, motion
& temporal reasoning

Research-designed video sequences and tasks covering motion, temporal structure, physical consistency, and long-horizon dynamics.

VIDEOMOTIONWORLD MODELS
03 / DATA PROGRAM↗
SPACE / EMBODIMENT

Robotics &
embodied data

Action trajectories, demonstrations, object interaction, pose and task data for robotics and embodied intelligence—grounded in real-world expertise.

SPATIALROBOTICSACTION
04 / DATA PROGRAM↗
SIGNAL / EVALUATION

Evaluation &
learning environments

Capability-focused benchmarks, reproducible evaluations, automated quality checks, and expert feedback to measure data usefulness.

BENCHMARKSRL DATAVERIFICATION
✳

Not just more data.
Data designed to unlock the next model capability.

[03 / HOW WE WORK]FROM MODEL NEEDS TO VALIDATED DATA

Research-led.
Engineered.
Built to scale.

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.

THE OPIX DATA DESIGN → PRODUCTION LOOPEXAMPLE WORKFLOW / 001
STAGE 01 // DISCOVER●   SYSTEM VIEW
learning_brief.yaml
# Research with the model team
model_need: physical_reasoning
target_skills:
  - object_interaction
  - motion_prediction
failure_modes: to_investigate
success_metrics: jointly_defined
Start with the model capability gap—not a generic data quota.OPIX / LAB NOTE

* Illustrative production flow. Scopes, deliverables, and validation methods are tailored to each engagement.

[04 / THE TEAM]RESEARCH × ENGINEERING × INDUSTRIAL EXPERTISE

One lab.
Three kinds
of expertise.

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.

01 ↗

Researchers.

Work with clients to identify model learning needs and design capability-aligned data.

THE LEARNING OBJECTIVE
02 ↗

Engineers.

Turn research designs into reliable pipelines, scalable production, and automated QA.

THE PRODUCTION SYSTEM
03 ↗

Industrial
Experts.

Bring robotics, operations, physical processes, and domain knowledge into data creation.

THE REAL-WORLD CONTEXT

Research-informed by design. Engineered for scale. Grounded in the real world.

THAT'S THE OPix DIFFERENCE.
[05 / THE NEXT CONVERSATION]BETTER DATA STARTS WITH A QUESTION ↗

Let's build
what's next.

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.

START A CONVERSATION