Siloed Traditional Supply Chain Workflows Make
Execution Beyond Human Capacity

Consider the world of inventory management systems today. A supply chain team must set a Periodic Automatic Replenishment or PAR Level, which is the target inventory level for every SKU in every point of storage where the SKU is being stored (warehouse, hospital, etc.). Next, they’re expected to add a reorder quantity for each SKU at each of the points of storage. This translates into setting millions of parameters for each of the supply chain use cases described above. Making sense of all this data to determine the millions of parameters which then must be updated with exceptions is absolutely overwhelming and beyond human capacity to say the least.


The supply chain team for a typical food distributor or for a food manufacturer running their supply chain to directly deliver to retail store i.e., applying a Direct Store Delivery (DSD) model, has to regularly procure and/or produce thousands of unique products, each managed through a unique Stock Keeping Unit (SKU). Managing a complex supply chain composed of tens to hundreds of warehouses, each covering a geographic location or region, the team has to decide how much to store of each item across each warehouse. Furthermore, the team has to forecast continuous per-product demand imposed on each warehouse from each of the hundreds or thousands of outlets serviced by the warehouse.


On a very similar note, the supply chain team for a typical healthcare system has to regularly procure anywhere from one hundred thousand to two hundred and fifty thousand different supply items, between surgery supply, pharmaceuticals, and consumable goods, from hundreds of suppliers. Once supplies are received, the team has to decide how much to store of each item across the main hospital warehouse and the numerous points of use. Obviously, things become even more complex for healthcare systems with multiple facilities, some with different Enterprise Resource Planning (ERP) systems being implemented across the different facilities.


The supply chain for an airline company consists of not only spare parts needed for maintenance and repairs but it also includes the operations that are essential to running a successful airline. Food items, for example, must be managed and with numerous flights leaving to virtually limitless destinations, the task to manage procurement and inventory in an efficient manner becomes an impossible task.

Industries with Supply Chain Optimization Opportunities


Consumer Products



Life Sciences

Wholesale Distribution

Aerospace & Defense


Public Sector




Oil & Gas


Future Cities

Seeloz is solving the disconnect between ERP and systems managing procurement. In the food industry, it is the disconnect between point-of-sale systems and ERPs that’s causing massive issues in the procurement and management workflows. In healthcare, it is the disconnect between hospital management systems and ERPs resulting in massive amounts of pharmaceutical waste. And in the airline industry, the disconnect between aviation systems tracking flights and the procurement of food and spare parts leads to the inefficiency of maintenance, repair, and operations of an airline’s assets.

SCAS represents a layer of smartness bridging the current gap between the ERP systems and the other technology systems managing customer data e.g., POS. It allows key managers to run their day-to-day operational workflows (and particularly procurement and inventory management workflows) driven by a solid AI-driven understanding of their respective end customers’ current and forecasted needs (at the per-product per-customer-location level). Building on this solid end-to-end understanding, SCAS applies a mix of AI-Driven Decision Support and Al-Driven Automation mechanisms to empower all players within the organization to drive efficiencies in their respective areas.