ICONOCI's z!™ Fulfillment is the only scalable and reliable real-time fulfillment planning solution to comprehensively meet the needs of complex high-volume commerce. It optimizes per order fulfillment within milliseconds while considering customer, supplier, material, capacity, transportation, shipment, storage, distribution, and production constraints. This results in multiple choices of realistic, specific delivery date promises and dynamic prices for the end-consumer during browsing and a profit-maximized order fulfillment plan for the vendor.

The following illustration depicts typical e-business component interactions. Items in terra-cotta are within the domain of z!™ Fulfillment.

z!™ Fulfillment is designed to address the limitations of existing fulfillment planning systems and achieve the highest possible performance while maintaining extremely high availability at a minimum hardware cost. z!™ Fulfillment solves real-time fulfillment planning by distributing both data and processing across commodity hardware. z!™ uses advanced networking protocols to achieve scalability across clustered machines running Windows NT 4.0 or Windows 2000 on industry standard hardware and readily available network technologies. In the near future, z!™  Fulfillment will offer support for Linux and other mainstream UNIX implementations.

Distributed in-memory data model and algorithms: z!™ Fulfillment uses a compact distributed in-memory representation. It incorporates components such as bills of distribution (BOD), and bills of materials (BOM), as well as the business rules needed to implement available-to-promise (ATP), allocated-available-to-promise (AATP), and capable-to-promise (CTP) functionality. z!™ Fulfillment can represent a very large problem in a very small space. ICONOCI's fast proprietary parallel processing algorithms take advantage of the compact representation, allowing significantly faster optimization time and orders of magnitude higher throughput.

Partitioning and clustering architecture: z!™'s dynamic partitioning allows problem sizes to grow many times larger than what can be supported by leading supply chain management (SCM) or enterprise resource planning (ERP) vendors, while providing orders of magnitude faster fulfillment planning for complex supply chains. z!™'s replication and clustering technology provide fault tolerance and continuous availability that is lacking in leading SCM vendors' memory resident data models.

Architecturally, z!™ can be viewed in three tiers:
  z!™ API (Application Program Interface)
  z!™ Coordinator
  z!™ Solver Clusters

z!™ API
Users of our z!™ interface via asynchronous function calls to z!™ API - a comprehensive set of C function calls that perform problem specific requests. For example, for fulfillment planning these include customer requests such as quotations, orders, cancellations and reservations, and also vendor updates to the supply availability.

z!™ API can be integrated within user applications using XML, Java, CORBA or COM objects. The interface between z!™ API and z!™ Coordinator is many-to-many via protocols that run on top of TCP/IP.

z!™ Coordinator
z!™ Coordinator performs two primary functions:
 - distribution of requests to the solver clusters
 - global optimization of the fulfillment algorithms

The interface between z!™ Coordinator and z!™ Solver Cluster, and within the solver clusters is via ICONOCI's innovative clustering protocol - z!™ Net.

z!™ Solver Cluster
z!™ Solver Cluster consists of two components:
 - z!™ Master
 - z!™ Replica

z!™ Net facilitates failure detection, fail over and role changes. For example, if a master fails one of the replicas will dynamically assume the role of the master, with no visible impact to the customer.

Exceptional performance, at a modest cost in hardware and support, is the main benefit of the z!™ architecture. z!™ Fulfillment capitalizes on this performance by offering several distinct capabilities that cannot be duplicated by any other product on the market.

	Increased cost savings by optimizing over a larger portion of the supply chain while maintaining sub-second response times.
	Increased browser-to-buyer conversion ratio by generating multiple availability quotes for every product on every page-view during the browsing process.
	Optimization of gross profit margins during browsing by utilizing dynamic pricing based on real-time supply, demand, cost, and capacity variables.

1. Assumes 30 time buckets, 10 locations and 1 customer class. Up to 50 million products.
2. Available in future releases.