Wholesales

Demand from B2B, e-commerce and marketplaces has a different characteristic than orders from key audiences (e.g. Amazon, networks). If you throw these signals into one bag, you get chaos, cannibalization of sales and extinguishing fires.

Nadii distributes streams and guides each according to its logic: builds forecasts and replenishment policies per channel and per strategic customer with its own SLA parameters, shipping dates and priorities, and the inventory reserves intelligently — what is assigned to the contract does not disappear on e-commerce (and vice versa).

Our AI models — developed by ML specialists with the title Kaggle Grandmaster — learn the influence of specific factors on demand (weather, price and cost of delivery, promotions and discounts, exposure to the list of products, opinions, actions of competitors) and automatically improve, so that forecasts adapt to changes and decisions are increasingly precise. When the risk of lack of stock arises, Nadii weighs the margin, penalties for non-compliance and the risk of losing a customer and chooses the best allocation. Where the forecast does not give you an advantage (frequent deliveries, small MOQ, high reliability), Nadii allows you to switch to on-demand mode; when conditions change (lead times increase, penalties increase), the system automatically switches to a predictive or hybrid approach.

What you gain:

• stable service of key customers without limiting other channels,
• less manual interference — channels do not fight for the same stock,
  
• higher margin and more confident decisions thanks to AI predictions that They learn and improve over time,
• precise allocations.

In wholesale, one SKU does not equal the other. In addition to strategic items, we have replacements, products with expiration dates, kits and own brands. Nadii organizes this chaos “from the general to the detail.” For each SKU in any location keeps a status (e.g. active, for sale, on order, discontinued) — synchronizing it with the ERP or managing it independently — and shows the results and movement of goods by statuses. In parallel, the system leads life cycle: ramp-up (new), season (maintaining availability), ramp-down (controlled extinction), automatically adjusting ordering policy and reporting.
For time-sensitive items, Nadia signals risk beforehand, suggests Transfers instead of disposal and — when it's worth it — controlled markdowns. In the case replacements maintains service without doubling stock. At sets/sets coordinates the demand for the complete set and for the components so that the lack of one element does not block sales; it also supports simple picking. Own brands can get their own availability targets and stock policies, and reports show the cost of maintaining a position in the offer (capital + excess risk) and its impact on margin — black and white.

What you gain:

• Less “dead” inventory and expired products — earlier signals, the right moment of the last order and transfers instead of disposal.
  
• More sales without bottlenecks — substitutes maintain service, and kits do not stop due to lack of component.
  
• Capital works where it makes money — statuses per location plus the cost of maintaining the position lead to conscious limitations and the right depth of the offer.
  
• Greater availability of what is strategic — clear priorities for key SKUs and private brands.
• ‍Less manual work, more predictability — statuses and life cycles are systemic, alerts appear only where intervention makes sense.

The purchasing budget, the target inventory level (value or weeks of coverage), the expected cash flow and customer priorities easily “diverge” in the thicket of thousands of decisions: how much, when and where to order, what to reserve for whom, which deliveries to speed up. Nadii coordinates all this into a single, systemic process. At the management layer, you set the policy: budget limit and inventory cap (globally and per category/own brand), availability goals, channel and customer priorities, presentation inventory rules, and rules for time-sensitive items.

To better set goals and plan resources, Digital twin can simulate warehouse load, showing the optimal balance between inventory, availability, smart buying and operation costs and how specific limits affect P&L. Behind the scenes Nadia's cost-probabilistic engine translates these objectives into micro-decisions: each procurement and allocation proposal weighs the risk of shortage (lost margin, penalties for non-compliance with standards, risk of loss of customer) against the cost of excess (capital, risk of overdue, location and transport) and the impact on the result. You have the choice of mode tough (strict budget/stock limits), supple (pursuit of a goal in the interval) or hybrid — e.g. a hard limit for the entire company with exceptions for strategic categories or campaigns. Nadii calculate the optimum every day - and when necessary more often — and automatically adjusts decisions when demand, delivery times, prices, odds or promotion calendar changes. Report genesis of the result shows the “why”: what proportion of P&L and inventory results from forecasting, smart buying, supplier delays, capacity limitations or exposure requirements — including situations where “high” inventory is optimal because it secures a planogram, campaign or delivery dates.

What you gain:

• No more yo-yo effect between availability and inventory — microdecisions are consistent with management and sales goals.
• Budget kept “from the slot machine”: orders are within the limit, choosing the best mix (margin, risk, service).
  
• Predictable impact on P&L — you know in advance how decisions will translate into outcome.
  
• Conscious trade-offs: You can clearly see the cost of +1% availability or an extra week of coverage — and whether it pays off.
  
• Transparency and accountability: a single source of data from management to operations, full tracking of decisions and their rationale.
• Less manual “tightening” at the end of the month — financial and operational goals are met on an ongoing basis.

In the warehouse, B2B teams and the sales, e-commerce, purchasing, logistics and finance departments look at the result from different perspectives — this is natural, because everyone is responsible for a different part of the goal. This leads to different priorities and multiplying reports, which makes it easy to lose what is most important operationally “for today”.

Nadii organizes it in a single, easy-to-read dashboard — without a “flood of data”, but with clear indicators and a list of actions to perform and tracking progress over time. The system shows the genesis of the result: forecast error vs. on-demand mode, purchasing decisions (e.g. purchases at a discount), delays and level of supplier service (On Time In Full), storage and transport limitations, as well as the impact of CFO limits (budget, inventory cap. Each recommendation has cost rationale — lost margin vs. cost of excess, cost of transportation and operations, risk of penalties for key customers — and full audit trail: who, when and why changed the decision. Data and decisions can automatically flow into BI/Data Lake; roles and powers enable management to see the macro picture, KMs to their customers, procurement to deliver quality, and operations to specific tasks and only those alerts that require intervention.

What you gain:

• One data source for B2B, e-commerce and sales: common KPIs (service, weeks of coverage, OTIF, inventory and cost of service and margin “per customer/channel”.
  
• End the flood of reports: one easy-to-read dashboard + list of activities, with the ability to track the implementation of plans over time.
  
• Faster decisions and fewer disputes: same fact base and reasoned allocations instead of “disputes over a better Excel file”.
  
• Alignment with finances: budget, stock limits enforced in daily decisions; visible trade-off (e.g. +1% availability vs. extra week of coverage).
  
• Less risk in relationships with key customers: clear SLAs, early signals about the risks and costs of penalties, clear “why” when allocating goods.
• Compliance and control: full change tracking and automatic reports defined at the beginning of the collaboration — with views for each management level (C-level, managers, operations)