Built for Global Importers and Wholesalers

Prosessed AI is a full stack operating system built specifically for B2B businesses, importers, wholesalers, distributors, and manufacturers. Think of it as the connective tissue between every part of your business: the orders coming in, the stock sitting in your warehouse, your field sales team out visiting customers, and the decisions your team makes every day.

Most businesses in this space run on a patchwork of spreadsheets, WhatsApp groups, and disconnected ERPs. Prosessed AI replaces that fragmentation with a single unified platform that connects demand (customers, orders, sales reps), supply (inventory, procurement, warehouses), and intelligence (analytics and AI driven recommendations).

Traditional ERPs are backend heavy systems built for record keeping and compliance. They are rigid, slow to configure, and not designed for the frontline reality of B2B commerce such as field reps placing orders, warehouse staff tracking batches, and customers wanting to reorder on mobile.

Prosessed AI takes an execution first approach. It makes daily operations faster first, then layers intelligence on top. The result is a system your team will actually use. It is also designed to work alongside your existing ERP rather than force a complete replacement.

Five tightly integrated modules share the same data:

Order Management System (OMS)

Order creation, tracking, credit enforcement, and pricing across every channel

Inventory and Warehouse Management

Real time multi location stock with batch and expiry tracking

Sales Representative App

Mobile first tool for field teams that works offline

B2B Commerce Platform

Self serve ordering portal for customers on web or mobile

Jerry AI

The intelligence layer for forecasting, recommendations, and automated communication

An order placed by a sales rep instantly updates inventory, triggers procurement recommendations if needed, and is visible to the customer in real time.

Faster order processing means more orders fulfilled daily without adding headcount. Better inventory accuracy reduces capital tied up in excess stock and prevents stockouts. AI driven procurement planning reduces emergency purchases at poor prices. Self serve ordering captures revenue that would otherwise be lost outside business hours. Sales visibility lets managers catch performance gaps while there is still time to act on them in the current period.

The OMS handles the full lifecycle of a sales order from placement through processing and fulfillment to tracking and completion. It supports multi channel order capture including sales reps, B2B portal, WhatsApp, and API, real time tracking, automated workflows, credit limit enforcement, and flexible pricing. It is designed to scale from 50 orders a day to 5000 while keeping workflows consistent and auditable.

Both run in parallel. Sales reps place orders through the app. Customers place orders through the B2B portal. All of them flow into the same OMS, giving a single consistent view of everything. The self serve channel is particularly valuable for capturing repeat orders outside business hours and reducing admin load on the sales team.

Yes. You can define multiple price tiers and assign customers to them, with individual overrides for specific customer product combinations. When a rep places an order or a customer logs into the portal, they see only the prices that apply to them pulled automatically from their profile with no risk of quoting the wrong rate.

Yes. Jerry AI interprets the WhatsApp message, confirms the details with the customer, and logs it as a structured order in the OMS. Your operations team sees a clean order instead of a screenshot to type manually. Many B2B customers already use WhatsApp with their suppliers and will not change that habit, so the platform works with it.

Each warehouse location has its own stock record and movements inbound, outbound, transfers are tracked as they happen. When an order is allocated to a specific warehouse, available stock there updates instantly. This prevents selling stock committed elsewhere and gives a unified view across all locations from one dashboard.

Yes, built in not an add on. Each batch is tracked separately with arrival date, expiry date, cost, and location. The system alerts you as stock approaches its expiry window and supports FEFO first expiry first out fulfilment to reduce write offs and ensure customers receive products with acceptable remaining shelf life.

Two layers exist. Configurable low stock alerts for operational control and AI driven purchase recommendations that factor in historical demand and lead times. This prevents both extremes stockouts that damage customer relationships and overstock that ties up cash.

Stock adjustments whether from a cycle count variance, a write off of damaged or expired goods, or a customer return being reinstated into available stock are processed as real time transactions in the system. There is no batch overnight run or manual recalculation required. The moment an adjustment is posted, it flows through to available stock, committed stock, and any pending order allocations that depend on that inventory.

This matters most in the gap between ordering and receiving. If your warehouse team conducts a cycle count mid week and discovers a variance on a product that has 10 open orders allocated against it, the system immediately reflects the corrected position. Order fulfilment logic can then flag orders that are now at risk rather than your team discovering the shortfall on the day of dispatch.

Returns from customers follow a similar logic. The returned goods are inspected, a condition is assigned such as resaleable, damaged, or hold for supplier credit and the system updates stock accordingly. Only goods marked resaleable re enter available inventory. The rest are quarantined with a reason code until disposed of. Every adjustment carries an audit trail including who made it, when, and why which is important both for internal controls and supplier claims on damaged goods.

It replaces notebooks, WhatsApp messages, and printed price lists with a single mobile tool. Sales reps can place orders with correct customer pricing loaded automatically, check real time stock before committing, log visits and notes, plan routes, and access invoice history all in the field. Works offline too, syncing automatically when connection is restored.

Every action is recorded centrally including orders placed, customers visited, routes traveled, and notes added. Managers get a live view of field activity without relying on manual reports. They can see which customers have not been visited recently, which reps are hitting targets, and where activity is dropping off while there is still time to act on it.

A large part of what most B2B sales teams do is order taking for established customers who want the same things they ordered last month. The B2B portal lets those customers self serve by browsing their catalog, seeing their pricing, checking credit limits, and reordering in a few taps. This shifts routine reorders off the sales team entirely and lets them focus on growing accounts and handling situations that genuinely need human engagement.

Pricing controls in the Sales Rep App work at the role level. A standard sales rep can only sell at the pre configured price for that customer. There is no field to type in a discount. If a rep wants to offer a price override they must raise it for manager approval which is handled as a workflow step rather than a verbal conversation that never gets recorded.

Managers can be granted a discretionary discount ceiling such as up to 5 percent below the customer's standard price without needing to escalate further. Any override above that ceiling requires a second approval from a commercial director or pricing team. Every approved override is logged with the reason code, the approver, and the order it applies to.

This creates a structure where the field team has some flexibility to close deals but within guardrails that protect overall margin. It also gives the commercial team visibility into how often overrides are being requested, by which reps, for which customers, and whether the discount pattern suggests a pricing tier needs to be renegotiated rather than constantly overridden on a case by case basis.

Jerry AI is the intelligence layer across Prosessed AI. It handles demand forecasting, smart inventory and procurement recommendations, automated customer follow ups via WhatsApp and voice, raw material planning for manufacturers, and conversational ordering interfaces. It learns from the operational data your business generates on the platform.

Supporting it. The AI handles data crunching, pattern recognition, and routine follow up not the complex judgments that experienced people make. A procurement manager still decides whether to follow a purchase suggestion. A sales manager still sets priorities. Jerry AI is the well briefed analyst working in the background not the decision maker.

It learns from your own operational data including order history, customer behaviour, stock movements, and procurement cycles. The execution first philosophy exists precisely for this reason because clean structured operational data is the foundation the AI needs to be useful. Businesses that try to implement AI before their data is clean get poor results. Prosessed AI is designed to avoid that by digitising operations first.

A straight average of historical demand is one of the least useful inputs for wholesale planning and Jerry AI does not rely on it. The forecasting model separates baseline demand from seasonal patterns and one off events. A spike in December for a product that sells steadily the rest of the year is treated as a seasonal signal. The model increases the forecast for the equivalent period next year rather than raising the annual average.

Promotions are handled as tagged events in the system. When you run a promotional period you mark it as such which allows the model to exclude that spike from the baseline forecast and instead treat it as an event driven uplift. If you plan to run the same promotion again you can instruct the forecast to include the promotional uplift for that future window.

Outliers such as a one off bulk order from a customer that does not reflect recurring demand can be excluded or downweighted so they do not skew future recommendations. The model also gets more accurate over time as it accumulates more of your business specific history which is why forecast quality in month 12 is meaningfully better than in month 1.

Pricing is structured around the modules you use and the scale of your operation. You can view base plans on the pricing page or speak with the team for a proposal tailored to your specific configuration particularly relevant for larger or multi entity deployments.

Yes, you can get started for free and explore the platform before committing. For businesses evaluating a larger rollout a guided pilot with implementation support is typically the better path. Reach out to the team to arrange it.

Core OMS and Sales Rep App deployments can go live within days to a couple of weeks. More complex configurations such as multiple warehouses, ERP integrations, or custom pricing take longer. The platform is configured not coded which keeps timelines significantly shorter than traditional ERP projects. Most businesses are processing live orders within weeks not months.

ERP integration is one of the most commonly underestimated parts of any software deployment and it is worth being concrete about what it involves. Prosessed AI connects to existing ERPs via API and has built integrations with common systems including SAP and Infor. The depth of integration such as what data flows in which direction and how often is scoped during the onboarding process based on what each side of the system owns.

A typical configuration has Prosessed AI handling the frontline operational layer including order capture, inventory tracking, sales rep workflow, and customer communication while the ERP remains the system of record for finance including general ledger, accounts payable, and statutory reporting. Data flows between the two on a defined schedule. Orders confirmed in Prosessed AI are posted to the ERP. Stock receipts recorded in the ERP are reflected in Prosessed AI.

The Prosessed AI implementation team handles the configuration on their side. Your IT team or ERP partner handles any configuration required on the ERP side. The scope of that work depends on how standardised your ERP configuration is and whether your ERP vendor API is accessible. For systems with limited API access or heavily customised ERP environments the integration scope and timeline should be discussed explicitly before committing to a go live date.