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PRANINNOVATIONSProduction Specialists

Physical AI

A detection nobody acts on is not worth having

The model is rarely the hard part. Getting its output into a controller, a work-order queue or a shift report — reliably, at 3 a.m., with no one watching — is the work most vendors leave to you.

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Production architecture for the Vision Systems Integration practice

Vision Systems Integration

The situation

Before we start

01

Results that stop at a dashboard

A screen nobody watches changes nothing. Detections have to reach a reject gate, a work order or a supervisor to matter.

02

Equipment older than the engineers maintaining it

Plant floors run controllers installed decades ago. We integrate with what is there instead of requiring you to replace it.

03

One more system to babysit

Every addition is an operations burden. We integrate into the tools your team already opens.

What working means here

Signed first. Measured after.

The value of each one is set with you during scoping, from your data and your line. What does not change is that they are written down first and published against afterwards, pass or fail.

  1. 01

    Acceptance tests passed

    Every interface exercised on commissioning day, against the behaviour agreed in writing

  2. 02

    Fail-safe drills

    Network loss, obstructed camera and device failure each rehearsed before go-live

  3. 03

    Time to restore

    From an alert to the line running again, measured during the supervised period

How it is assembled

Stage by stage

Each one ends in something you keep.

  1. Step 01

    Survey what is installed

    Controllers, camera estate, network segments and the conventions your integrators already follow.

  2. Step 02

    Specify the hardware

    Cameras, lenses, lighting and enclosures chosen against the measurement the process actually requires.

  3. Step 03

    Design the interfaces

    Tag maps, event schemas and fail-safe behaviour, reviewed with your controls and IT teams before build.

  4. Step 04

    Bench test, then commission

    Proven against a rig first, then installed in a planned window with acceptance tests run against the agreed behaviour.

  5. Step 05

    Train and hand over

    Operator training, runbooks and a documented escalation path.

Scope

What the work includes

  • Survey of installed controllers, camera estate and network segmentation
  • Camera, lens, lighting and enclosure specification
  • Interface design against your existing tags, schemas and conventions
  • PLC and SCADA integration over OPC UA, Modbus or vendor protocols
  • MES and video management system integration
  • Fail-safe behaviour on network loss, device failure and degraded input
  • Operator interfaces designed with the people who use them
  • Commissioning, acceptance testing and operator training

Deliverables

What you keep

  1. 01Integration design and tag map
  2. 02Specified and installed camera hardware
  3. 03Working interfaces to controllers and plant systems
  4. 04Documented fail-safe behaviour
  5. 05Commissioning and acceptance test record
  6. 06Operator training and runbooks

Typical stack

OPC UA · Modbus TCP · MQTT · ONVIF / RTSP · Milestone & Genetec APIs · Ignition · GigE Vision

Construction · Vision

Zone and PPE monitoring across eleven active sites

Site cameras were recording for insurance but nobody was watching them live. We added edge units behind the existing camera estate to flag exclusion-zone entries and missing PPE, and routed alerts to the supervisor on shift.

Read the engagement
11
sites live on existing cameras
99.9%
per-site availability
< 4 s
detection to supervisor alert

Start

How Vision Systems Integration begins

From $60K, scoped per line or cell

Where an engagement lands inside its band is set by data readiness, integration depth, the reliability bar, evaluation burden, deployment constraints and usage economics. All six, explained.

Thirty minutes on the problem and where it happens, then a fixed-price pilot if it looks like a fit.

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FAQ

Asked before signing

Only with your controls team's agreement, and only through the segmentation they specify. In most plants we sit on a separate network and write to the control layer through a single reviewed interface.

Fail-safe behaviour is designed and documented before commissioning, usually a fall-through to the existing process plus an alert. It is part of acceptance testing.

Regularly. We handle the vision and AI layer, they own the controls work, and the interface between the two is specified in writing so neither side guesses.

Often paired with

Where this fits with the rest

  1. 01Physical AI

    Edge AI & Computer Vision

    Detection, inspection, tracking and safety on-device. Milliseconds, and no network dependency.

  2. 02Physical AI

    AI IoT Development

    Sensor fusion, predictive maintenance and condition monitoring across a fleet you can update.

  3. 03Operate

    Managed Edge & Model Fleet

    Drift, retraining, OTA rollout, device health and uptime reporting, under an agreed SLA.