Question 1

Is predictive maintenance worth the AI investment?

Accepted Answer

For some asset classes yes; for many, procurement AI delivers more ROI faster. We help size both: predictive maintenance for high-value asset bases with rich sensor history, procurement AI for spend bases over $200M. See [AI procurement material cost reduction](/insights/ai-procurement-material-cost-reduction-2026).

Question 2

What blocks manufacturing AI deployments?

Accepted Answer

Most commonly the data layer. Sensor histories are sparse or misaligned, MES events are missing, supplier masters are duplicated. AI readiness work is mostly data foundation work.

Question 3

What is the AI readiness engagement timeline?

Accepted Answer

30-day Analytics Truth Audit ($35,000 fixed) covers the diagnostic. Implementation typically runs 12 to 24 weeks at $150,000 to $440,000 depending on the workload count and plant footprint.

Question 4

What does AI readiness actually mean?

Accepted Answer

AI readiness means the data foundation is clean enough, the governance is defensible enough, and the metric layer is consistent enough that AI deployment lands without producing the kind of hallucinations or compliance issues that block production use. The work is mostly at the data layer.

Question 5

Do you build AI models or just the data layer?

Accepted Answer

We focus on the data foundation that supports AI deployment. Model selection, training, and tuning we coordinate with the client's AI team or specialist partners. The data layer is where most AI pilots stall.