AI-native operating readiness for new factories
A new factory needs an operating team and usable data systems. We help business, engineering and HR teams design how people, AI and systems work together, while organizing assets, processes and data for professional computation. Hiring, training, system configuration and initial applications advance around the same operating tasks, enabling AI to create operating value from the first day of production.
Hiring criteria, team training and system choices are established before production starts. Designing AI participation at this stage aligns people and technology around the same operating goals, with applications prepared alongside the work.
Simulated workflow: recommend, then approve. The operating mode is configured for the task.
After feed preparation is revised, this example uses 288 rather than 312kWh for the same 12t output; waiting falls from 8 to 2 minutes. The engineer reviews these simulated results.
The axis shows elapsed time within each trial; both produce 12t.
L-02 meter scope; same trial batch; Crew records mark feed waiting
The 23kWh/t trial reference is predefined in this example
Read trial and crew recordsRead trial batch T-06 and crew records✓
Compare electricity use with waiting periods10:10 and 10:15 exceed reference; read idle-wait events✓
Draft the crew check taskDraft a crew check task, requiring engineer approval✓
Operating preparationEngineer review · crew trial training
Data preparationMeter · batch · waiting events
Together they support this trial taskAI drafts; the owner confirms before action.
Engineer approves preparing feed before starting this stage; the crew trials the revised handover
Example feedback recordedAfter the revised handover, the simulated matched-load trial records 288kWh / 12t = 24kWh/t and waiting falls from 8 to 2 minutes. The engineer reviews this illustrated comparison.
Space plays/pauses; arrow keys seek.Reduced motion is on. Explore the complete work with the timeline.
Before production, select one task with reviewable inputs, calculations and responsibilities. AI reads records, runs the calculation and drafts a check; the engineer approves, the crew acts and reviews the next trial.
| Time | kWh | t | Crew event |
|---|---|---|---|
| 10:00 | 42 | 2.0 | — |
| 10:05 | 48 | 2.0 | — |
| 10:10 | 66 | 2.0 | Feed waiting |
| 10:15 | 62 | 2.0 | Feed waiting |
| 10:20 | 50 | 2.0 | — |
| 10:25 | 44 | 2.0 | — |
312 kWh ÷ 12.0 t = 26.0 kWh/t
L-02 meter scope; same trial batch; Crew records mark feed waiting
The 23kWh/t trial reference is predefined in this example
After the revised handover, the simulated matched-load trial records 288kWh / 12t = 24kWh/t and waiting falls from 8 to 2 minutes. The engineer reviews this illustrated comparison.
First task trial complete; engineer confirms continued use
Map everyday work such as handovers, operating analysis and exception follow-up, and define the required results. Decide where digital employees contribute analysis, records and tool use, and where people provide judgement and site action. Translate this into hiring criteria and training.
Prepare connections, asset definitions and records alongside engineering work. An electricity record needs a link to its asset, process and production period before it can support energy comparisons and professional calculations. Reuse suitable interfaces and add collection for the intended applications.
Bring both tracks into the first tasks. On a configured schedule, the system retrieves records and runs suitable models; digital employees organize the analysis and recommended actions for approval. Results return to the relevant assets, processes and periods to inform the next analysis. During commissioning, users practise checking evidence and handling exceptions, preparing the products for everyday use at startup.
Plan construction, hiring and commissioning readiness together. Retain selected equipment, business systems and customer expertise. Configure data, specialist computation and AI cooperation around the first tasks, adding capabilities that can enter everyday operation. Adopt selected products or a broader combination, with interfaces, operating modes and support agreed together.
Prior team experience in energy efficiency, supply–demand optimization, cross-factory improvement and material and process tracking informs task design and professional applications. We combine this experience with data, models and AI products that the new team can use, alongside the work design.
Bring the construction and startup schedule, hiring plan and the work you want to perform well from day one. Together we can coordinate operating and data readiness and select the first products and users.