Physical AI Humanoid Learning in Smart Factory

The Expertise Already Exists
We Make It Ready for Physical AI

02 / CHANGE

Manufacturing Never Stands Still

01

New Model

New product variants, model updates, and changing component specifications

02

New Process

Changes in process routing, station allocation, and assembly sequences

03

New Tasks

Changes in movements, tool handling, task sequences, and assembly methods

04

New Skills

New movement patterns, task-specific know-how, and adaptive work techniques

Every new model changes how work gets done

New products bring new processes, new tasks, and new skills to learn.

03 / PROBLEM

New Models Don't
Just Change Products
They Change the Work

0
TASK CHANGES / YEAR
22 Processes × 120 Model Changes Factory-scale estimate based on actual data
01

Process-Level Change

Changes cascade down to individual movements, tool use, task sequences, and timing on the assembly line.

02

No Factory-Floor Learning

Manufacturers still lack a practical way to capture real-world work and turn it into learning data for Physical AI.

03

Repeated Retraining for Every Change

Every model or process change triggers another cycle of training, validation, and adaptation.

04 / THE READYSTATE APPROACH

Turn Every Process Change
into Skill Data for Physical AI

SKILL DATA

ANALYZE

Analyze and Understand Real-World Work

Capture and analyze productivity, work patterns, cycle time, and manufacturing context.

TRAIN

Train Physical AI

Transform real-world work into structured Skill Data that Physical AI can learn from.

OPTIMIZE

Optimize Deployment

Validate Physical AI against real production conditions and optimize deployment as processes change.

READYSTATE transforms real-world manufacturing work into Skill Data for analyzing operations, training Physical AI, and optimizing deployment.

05 / SKILL DATA

It Starts with Understanding How Work Is Actually Done

Motion Data Computer Vision Pose Tracking

Motion Data

Captures human posture, joint movements, hand positions, tool paths, task sequences, and timing directly from real-world work.

+
Manufacturing Context MES & ERP Production System

Manufacturing Context

Connects human motion with work orders, product and process information, takt time, equipment data, and quality results from the factory floor.

=

Skill Data

Structured data combining human motion with manufacturing context for analysis, work comparison, process improvement, and Physical AI training.

Motion alone does not explain the work

By combining how people move with the manufacturing context behind each task, READYSTATE creates structured Skill Data for operational analysis, process improvement, and Physical AI training.

06 / OBSERVER + GRAPE

One System, from Real Work to Physical AI

READYSTATE transforms real-world manufacturing data into Skill Data for training, validating, and deploying Physical AI.

REAL WORK

Assembly line operations

OBSERVER

Capture work
Create Skill Data

SKILL DATA

Motion data + Manufacturing context

GRAPE

Analyze·Train·Optimize

PHYSICAL AI

Ready for real production

OBSERVER

Combines motion data with manufacturing context on the factory floor to generate structured Skill Data from real work.

VIEW OBSERVER DETAILS

GRAPE

Enables production managers to validate, train, deploy, and adapt Physical AI using Skill Data from real manufacturing processes.

VIEW GRAPE DETAILS
07 / OUTCOMES

Improve Today's Line
Make Physical AI Ready for Production

TODAY'S OPERATIONS

Manufacturing Operations

Higher productivity, better line balance, and faster adaptation to change.

01

Higher Productivity

Identify more efficient work patterns by comparing how tasks are actually performed.

02

Better Line Balance

Balance processes by identifying bottlenecks, workload differences, and cycle-time variation.

03

Faster Adaptation

Adapt faster when new models, products, or process changes are introduced.

TOMORROW'S AUTOMATION

Physical AI

Physical AI training, validation, and production deployment using Skill Data.

01

Validated Capability

Evaluate Physical AI capabilities against real-world work requirements and Skill Data.

02

Faster Training

Accelerate training and retraining with Skill Data grounded in real manufacturing context.

03

Production Deployment

Support production deployment by matching validated Physical AI capability with real process requirements.

08 / VISION

Train the Future

The People Who Know the Work Should Be Able to Teach the Robots That Will Do It.