Companies make pricing and customer decisions with broken cost visibility. Activity-Based Costing, Resource Consumption Accounting, and German GPK represent elegant methodologies promising accurate customer profitability analysis, yet implementation reality is brutal. Deploying sophisticated cost accounting demands expensive consultants, brittle integrations across ERP, MES, CRM, and WMS, and continuous maintenance as business evolves. Advanced cost accounting remains a luxury for large enterprises while mid-market companies make critical decisions on flawed margin assumptions. The profitability blindness becomes acute in B2B operations where customer relationships exhibit extreme diversity—high volume with thin margins and specialized packaging, small frequent orders with customization, volume rebates generating support incidents. Without proper cost-to-serve allocation, companies cannot distinguish profitable relationships from subsidized ones. The market offers abundant CRM platforms and basic pricing tools, yet no system bridges cost intelligence with trade policy execution.

The intelligent cost allocation engine inverts this paradigm through bottom-up emergence from operational event streams. Rather than imposing predetermined structures, the system ingests business events as they naturally occur. ERP emits transactions, CRM generates interactions, WMS produces fulfillment events, MES reports production activities. This heterogeneous stream becomes the foundation for cost allocation mirroring actual operations rather than financial abstractions. The engine constructs activity graphs dynamically, mapping cost consumption to customers, products, and processes as they occur. Machine learning identifies patterns in event sequences, automatically inferring cost relationships without manual configuration. High support ticket volume associates service costs without explicit rules. Production changeovers correlating with variants flow setup costs naturally. The cost model self-tunes as business evolves—reorganizations automatically update cost flows, new products inherit structures from pattern similarity, process improvements immediately reflect in reduced allocations. Natural aggregation respects granularity visible in operational systems rather than forcing artificial precision.