A smart factory where AMRs, industrial robots and vision systems operate together.

OPTO PHYSICAL AI

Connecting the eyes and actions of manufacturing with Physical AI

We connect Vision AI, Mobility, Control, Metrology and Infrastructure in one verifiable operating loop.

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Approved BOMVerified configuration for the workload and site
Golden ImageStandard runtime and recovery baseline
FAT / SATFactory and site acceptance gates
DeviceOpsAssets, deployment, patches and audit trail
SLADefined operational responsibility

WHY NOW

Model accuracy alone does not solve production problems

OPTO closes the gaps across data, legacy equipment, safety, quality and lifecycle ownership.

01

PoC Gap

A demo works, but takt time, exceptions and operating ownership remain undefined.

02

Data Scarcity

Rare defects and expensive labels limit purely data-driven training.

03

Legacy Equipment

Cameras, PLCs, sensors and MES run on disconnected interfaces and lifecycles.

04

Safety & Quality

AI decisions must not blur safety control or metrology traceability.

05

Lifecycle Cost

Patching, OTA, RMA, security and training need a long-term owner.

INTEGRATED LOOP

One Physical AI loop from perception to operation

We design a verifiable flow of data and machine action instead of listing standalone boxes.

  1. 01PerceiveSense

    Acquire camera, 3D, thermal, spectral and equipment data.

  2. 02DecideDecide

    Combine AI and rules to produce evidence-backed decisions.

  3. 03ActAct

    Execute robots, machines and material flow within safety boundaries.

  4. 04VerifyVerify

    Validate outcomes with metrology, FAT/SAT and KPI gates.

  5. 05OperateOperate

    Manage the lifecycle through DeviceOps, SLA and training.

BUSINESS PORTFOLIO

Six business pillars, one execution system

Each pillar is a standalone offering and combines into an integrated Physical AI system when needed.

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A manufacturing line where an industrial robot and camera inspect products. A

Vision AI

AI & Machine Vision

Keep existing cameras and equipment while connecting inspection, deployment, data and reporting in one loop.

OutcomeTraceable inspection operations from camera input to quality reporting
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Autonomous mobile robots transporting pallets in a warehouse. B

Mobility

AMR & AGV Mobility

Orchestrate heterogeneous fleets, traffic, charging, WMS/MES interfaces and site safety.

OutcomeVisible and standardized multi-vendor robot operations
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A control cabinet with PLCs and industrial edge computers. C

Control

Physical AI Control

Connect AI prediction and optimization while preserving the authority of safety PLC and motion control.

OutcomeSafe AI action and data access for brownfield equipment
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An inline system measuring 3D geometry and surface data. D

Metrology

Inspection & Metrology

Quantify surface, geometry, thickness and thermal conditions while preserving metrology traceability.

OutcomeQuality data connecting calibration, recipes, SPC and lots
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Industrial edge computers and servers on a factory network. E

Infrastructure

AI Infrastructure & Trade

Validate compute, I/O, thermal, security and trade compliance rather than selling GPU specifications alone.

OutcomePredictable delivery and operations based on approved BOM and Golden Image
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Engineers operating and training on manufacturing automation in a demo lab. F

Services

Services, Training & Care

Discovery, PoC, FAT/SAT, training, SLA and improvement reports bring technology into sustained use.

OutcomeSustainable operation with standard deliverables and training
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INTEGRATED SCENARIO

Inspection, control, mobility and operations for battery and film lines

The architecture is organized around customer-visible outcomes from material measurement to operational traceability.

  • Inline measurement
  • Root-cause traceability
  • Safe machine action
  • Automated material flow
  • Operational history
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  1. 01

    Material

    WebGauge · SurfaceMetrix

    Inline measurement and process variation

  2. 02

    Vision

    InspectAI · Fusion3D

    Low-data defect inspection and sensor fusion

  3. 03

    Control

    EdgeLink · PredictCare

    Safe equipment integration and anomaly signals

  4. 04

    Mobility

    FleetOS · OmniMove

    Material flow, traffic and charging

  5. 05

    Operate

    DeviceOps · QualityOS

    Model, calibration, asset and lot history

TARGET VERTICALS

Repeatable industry recipes over one-off demos

We structure pains, interfaces and verification criteria before the PoC.

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CUSTOMER JOURNEY

Explicit KPI gates from discovery to operations

We define the problem and ownership first, then agree on deliverables and acceptance criteria for each phase.

  1. 01
    Site diagnosis

    Discovery

    Define ROI, KPI, data, equipment and safety conditions.

  2. 02
    Feasibility

    PoC

    Validate samples, models, takt and false decisions.

  3. 03
    Line integration

    Pilot

    Verify approved BOM, FAT/SAT and operating procedures.

  4. 04
    Production deployment

    Roll-out

    Apply standard configurations, training and change control.

  5. 05
    Improve

    Operate

    Run DeviceOps, SLA, calibration, model and security reviews.

Accuracy, takt time, false decisions, downtime and operating ownership are defined as separate contract gates.

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INSIGHTS

Practical resources for verification and operation

Decision criteria for the factory floor, not technology theater.

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START WITH THE PROBLEM

Let us define the factory problem first

Share the equipment, data, KPI and timeline. We will propose the right verification path.

Paid discovery

Assess the line, data, equipment and safety conditions and define the KPI.

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