Overview

Retalon Com is a unified analytics platform that uses artificial intelligence and machine learning to support retail decision making. The company presents itself as a one‑stop shop for planning, financial modeling, merchandise optimization, assortment control, and open‑to‑buy budgeting. Information about pricing or public case studies is not supplied on the website, so potential users will need to reach out for a custom quotation.

The financial component takes structured sales, cost, and inventory data as input. From those data it builds full‑life‑cycle financial projections that include revenue, gross margin, and cash‑flow estimates. By adjusting inputs such as selling price, cost, or order quantity, the tool shows how changes impact profitability. This feature is designed for store managers, merchandisers, and finance teams who need a quick view of the financial consequences of inventory decisions, but the lack of displayed sample outputs limits insight into the exact layout of the dashboards.

Merchandise planning is driven by sales history, inventory status, and planned buying quantities. The system processes these inputs to recommend optimal order sizes that aim to increase gross merchandise return on investment (GMROI). The output typically appears in recommendation tables that compare current orders to suggested quantities, and the platform claims to automate order creation. This capability is useful for mid‑volume retailers that want to reduce manual SKU analysis, yet the listing does not clarify the level of detail in the recommendations or whether the outputs integrate directly with purchasing systems.

Assortment planning has two layers. On a network level it analyzes SKU performance to advise when to shrink or expand the product basket. On the store or cluster level it refines assortment sizing by evaluating local demand patterns. The tool expects inputs such as store sales, inventory levels, and predefined store clusters, and outputs clustered assortment plans that include suggested SKUs to add or remove. The description reaches no further to mention how these plans interface with point‑of‑sale data or store management systems.

Open‑to‑buy budgeting automation is presented as a module that calculates the buying budget based on forecast demand, lead times, and available capital. The system ingests demand forecasts, inventory snapshots, and financial constraints, then produces a documented budget that can be used by buyers.