Production-process fluency
The team reads line changeovers, kitting logic, and WMS practice — not just robot kinematics.
Delivery
Ten stages. Acceptance gates at every one.
Industrial deployments fail on scope, interfaces, and acceptance criteria — not on robot capability. The process below makes each of those explicit before engineering spend begins.
01
Requirement assessment
Flows, volumes, containers, exceptions, and the business case.
02
Site survey
Layout, aisle, rack condition, floor, traffic, power, and network.
03
Technical proposal
Configuration, scope boundaries, acceptance criteria, and cost.
04
DFM & engineering
Interface design, skill configuration, safety zone definition.
05
Manufacturing & assembly
Platform build, integration, and internal test.
06
FAT
Factory acceptance against agreed criteria, with customer witness.
07
Installation & commissioning
On-site installation, calibration, and integration with live systems.
08
SAT & acceptance
Site acceptance test in production conditions, signed off.
09
SOP & training
Operating procedures, operator training, escalation paths.
10
Lifecycle support
Maintenance, spare parts, exception response, continuous improvement.
Stage content and duration depend on site scale and interface complexity. Deliverables for each stage are written into the project agreement.
Why this matters
Delivery is part of the product.
A Physical AI system only creates value when it runs inside your process, your safety rules, and your IT landscape. Engineering discipline at each stage is what makes the pilot repeatable.
Engineering execution
Interface development, safety zoning, and acceptance testing done by the same team that configured the skills.
On-site delivery
Commissioning and SAT executed on the customer floor, with operators trained before handover.
Start with a line assessment.
A structured assessment of your material flow, containers, systems, and safety constraints — with a written scope, acceptance criteria, and clear go/no-go.