Deployment

Make robots
intelligence-
ready

Connect the robots already at work - and the ones being installed next - to the data and infrastructure needed for Physical AI.
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Industrial robot arm in a factory cell, instrumented for data capture
Industrial deployment visual
Two deployment paths / One infrastructure

Start with the robot you have.
Or the one you need.

Different robot form factors and tasks need data from the work itself. XPhi’s deployment approach brings sensing and data capture closer to the robot, whether the cell is already running or newly designed.
01 / Existing installations↗
Existing robot cells with added sensors
BROWNFIELD

Upgrade the installed base.

Instrument existing factory robots and their workcells with suitable vision and other sensors. Capture robot-native observations alongside available controller and process signals, without assuming one retrofit fits every machine.

  • Assess the cell, task and integration constraints
  • Place sensors around the action that matters
  • Start with visibility and data; expand by validated use case
02 / New installations↗
New robot cell designed with sensing from the start
GREENFIELD

Design for learning from day one.

Work with factories, OEMs and integrators on new robot deployments so sensing, data interfaces and evaluation needs are considered as the cell is designed.

  • Plan camera, sensor and controller access up front
  • Build data capture into deployment workflows
  • Create a path for future model evaluation and upgrades
The deployment stack

From robot action to usable intelligence.

The aim is a continuous, governed path from physical work to better understanding — then, where the task and safety case support it, more capable robot behavior.
01 / DEVICES

Instrument

Vision and task-relevant sensing at the robot, tool and workcell.

02 / DATA

Capture

Time-aligned robot actions, observations and available process context.

03 / DATA ENGINE

Curate

Ingest, synchronize, quality-check, label and prepare task-relevant datasets.

04 / APPLICATION

Apply

Support factory insight, model evaluation and carefully gated autonomy work.

The same data path can serve operations and model development.Explore the Data Engine →
Value to the factory

A reason to deploy
before autonomy.

A factory should get useful, measurable value while the data infrastructure is being established. The same capture systems that enable learning can also improve today’s operations.
We help transform every deployment into a source of better data, better operations and a faster path to autonomy.
01

Production visibility

Real-time cycle activity, timestamps and process variants for better investigation and higher line uptime.

02

Quality assessment

Use multiple observations to measure visible defects or deviations, with richer context from real-world data.

03

Data rights by design

Define sourcing, ownership, permissions, usage and revenue sharing upfront so data assets remain valuable as models improve.

The XPHI approach

Autonomy is earned
one workflow at a time.

Progress depends on data quality, model capability, task fit, safety validation and factory approval. Today’s deployment approach is designed to create those prerequisites.
01

Observe

Understand real operations, environment variations and edge cases.

02

Understand

Turn observations into structured datasets and task definitions.

03

Assist

Deploy models in supervised or shared-control modes.

04

Autonomy

Progress to higher levels of autonomy as data, safety and reliability targets are met.

Future commercial model
AUTONOMY-AS-A-SERVICE

For validated workflows, XPHI envisions outcome-based pricing where customers subscribe to autonomous task execution rather than just hardware, creating long-term value from continuously improving models.

Build with XPhi

Start with one robot.
Design for what’s next.

Tell us about your factory floor, the workflows you want to understand and the outcomes that matter to your plant.
TALK TO OUR TEAM→
Two collaborating white robot arms
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