AI Readiness for manufacturers. Plant-floor data, OT/IT integration, predictive maintenance, and AI use cases scoped before any model deployment.
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).
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.
30-day Analytics Truth Audit (a fixed price) covers the diagnostic. Implementation typically runs 12 to 24 weeks at a deliverable-based fee depending on the workload count and plant footprint.
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.
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.
, and the data and AI work we ship is designed to hold up under their review.