ConocoPhillips closed the Marathon Oil acquisition in November 2024[2], inheriting roughly 45 percent of AMPCO with no prior operating involvement. New governance. New reporting. Fresh questions at the Houston commercial desk on chartering, terminals, MRO, and allocation. The Fairmarkit case study shows AI-assisted spend analytics delivered 14 percent identified, 6 percent awarded, in six weeks on indirect spend[13]. The hypothesis: that discipline has not yet reached vessel chartering and terminal throughput, where the dollars are roughly 100x larger.
Fairmarkit is on record: tail spend automation identified 14 percent and awarded 6 percent in six weeks across IT, MRO, and industrial supplies[13]. The inferred gap is on vessel chartering, terminal throughput, and commercial allocation, where the spend envelope is roughly 100x larger. We want to test it against your measured state.
A demand signal enters at Demand Sensing. It exits at Settlement. Autonomously. In minutes. Then the next one enters. The loop runs 24/7.[16]
Every number below comes from deployed customer outcomes, not projections. Pick the shape closest to AMPCO's.
No single train methanol producer to name yet. Global lead logistics, F500 SAP native, and a global commercial vehicle OEM match the shape closely. Named references at the booth.
One AI-native platform. Demand sensing, inventory, dispatch, execution, freight settlement, sustainability reporting. All on one intelligence layer that sits above the systems you already own.







We bring the hypothesis, the experiment design, and the deployed case closest to AMPCO's shape. You bring the measured state. We leave with a scoped two-week experiment or a clear reason it is not the right time. Three questions shape what we bring.
If all three are already solved, that is the most useful answer. Bring one chartering lead, one MRO owner, and one commercial planner.