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Case Studies/Leading GCC Frozen Perishable Meat Distributor (Identity Withheld)

Leading GCC Frozen Perishable Meat Distributor (Identity Withheld) Case Study

From forecast to confirmed SAP orders automatically

HublerX deployed an AI agentic demand forecasting workflow that turns historical order data into per-customer WhatsApp suggestions and instantly creates confirmed SAP orders via API—eliminating manual planning and re-entry.

Leading GCC Frozen Perishable Meat Distributor (Identity Withheld)

Industry

Frozen Perishable Meat — Wholesale B2B Distribution

Use Case

AI Demand Forecasting & Order Execution (WhatsApp-to-SAP)

Scope

19 branches · 180+ salespersons · 3,500+ B2B clients · GCC + Egypt

Systems

WhatsApp · Email · SAP ERP · HublerX AI Agent

Zero

MANUAL SAP RE-ENTRY

Orders auto-pushed to SAP on confirmation

<60s

CONFIRMATION TO SAP

From customer WhatsApp confirm to SAP order

3,500+

B2B CLIENTS COVERED

AI demand suggestions delivered via WhatsApp

3 yrs

ORDER HISTORY ANALYSED

Per customer, per SKU — across all channels

Customer Snapshot

Leading GCC Frozen Perishable Meat Distributor (Identity Withheld)

Frozen Perishable Meat — Wholesale B2B Distribution

A large frozen perishable meat distributor serving hypermarkets, supermarkets, and HORECA accounts across the GCC and Egypt. The business sources fresh, chilled, and frozen meat, poultry, and seafood from 9 countries under strict cold chain constraints.

  • check_circle19 branches across GCC + Egypt
  • check_circle180+ salespersons serving 3,500+ B2B clients
  • check_circleERP: SAP (ISO 22000:2018, HACCP; fleet of 250+ delivery vehicles)

The Challenge

Fragmented coordination, invisible operations

Three years of customer order history existed, but it was scattered across WhatsApp threads, email attachments, and SAP records, forcing each forecast cycle to start from staff memory and manually assembled spreadsheets.

"We used to forecast by memory and hope for the best."

What was breaking

  • Disconnected demand data
  • Seasonality and non-linear patterns
  • Broken execution and feedback loop
  • Perishable risk exposure
  • Institutional knowledge dependency

Before vs. After

What changed with HublerX

Before HublerX

  • —Disconnected demand data
  • —Seasonality and non-linear patterns
  • —Broken execution and feedback loop
  • —Perishable risk exposure
  • —Institutional knowledge dependency

With HublerX

  • ✓Unify fragmented demand signals
  • ✓Generate per-customer, per-SKU suggestions
  • ✓Confirm on WhatsApp with structured actions
  • ✓Close the loop and improve each cycle
  • ✓Push confirmed orders to SAP instantly

How HublerX Solved It

The operational workflow

1

Ingest 3 years of orders from WhatsApp, email records, and SAP into a single customer/SKU-level view.

Unify fragmented demand signals

Unify fragmented demand signals
2

Model reorder cycles, quantities, seasonality, and recent velocity, constrained by shelf life and lead times.

Generate per-customer, per-SKU suggestions

Generate per-customer, per-SKU suggestions
3

Send SKU-by-SKU suggestions with CONFIRM/EDIT, capturing changes inline with a confirmation trail.

Confirm on WhatsApp with structured actions

Confirm on WhatsApp with structured actions
4

Feed edits and delivery outcomes back into the model so forecast quality compounds over time.

Close the loop and improve each cycle

Close the loop and improve each cycle
5

The moment a customer confirms, HublerX pushes the order to SAP via API — zero manual re-entry, zero delay, and a unique Order Reference ID logged against every transaction.

Push confirmed orders to SAP instantly

Push confirmed orders to SAP instantly

The Differentiation

Orchestrating Actions,
Not Replacing Systems.

HublerX deployed an end-to-end demand forecasting execution workflow that sits above SAP, converting historical order signals into ready-to-order, per-customer SKU suggestions and capturing confirmations directly on WhatsApp. Once confirmed, HublerX creates the SAP sales order via API with a unique Order Reference ID and full audit trail, eliminating manual re-entry and delays.

  • layers
    Works on top of existing systems — ERP, email, WhatsApp, and finance tools.
  • account_tree
    Handles operational workflows, not just data storage. Approvals, escalations, execution.
  • memory
    HublerX’s AI agent builds a living per-customer, per-SKU demand model using three years of order history, recent velocity, and seasonal patterns, with shelf-life and lead-time constraints embedded. It continuously improves by learning from customer edits and comparing suggested vs. confirmed vs. delivered quantities each cycle.

AI Agentic WhatsApp-to-SAP Demand Execution

HublerX runs the entire forecasting execution cycle end-to-end: it builds a living demand model, generates SKU-level suggestions per customer, delivers them via structured WhatsApp messages, captures edits and confirmations, and pushes a validated sales order into SAP instantly with a complete audit trail.

  • check_circlePer-customer, per-SKU pattern modeling using 3 years of order history plus recent velocity weighting
  • check_circleSeasonality logic for Ramadan, Eid, Hajj, and identifiable HORECA/menu cycles
  • check_circleShelf-life and lead-time constraints to reduce over-order risk before suggestions are sent
  • check_circleAutomatic SAP sales order creation via API upon customer confirmation, with unique Order Reference ID and timestamp

Measured Business Impact

Outcomes across every dimension

Zero

MANUAL SAP RE-ENTRY

Orders auto-pushed to SAP on confirmation

<60s

CONFIRMATION TO SAP

From customer WhatsApp confirm to SAP order

3,500+

B2B CLIENTS COVERED

AI demand suggestions delivered via WhatsApp

3 yrs

ORDER HISTORY ANALYSED

Per customer, per SKU — across all channels

Operational Efficiency

  • Quote Turnaround42%
  • Request Processing3× faster
  • Re-entry Errors↓ 28%

Financial Control

  • Pricing ConsistencyHigh
  • Discount Leakage↓ 34%
  • Finance Approval Lag↓ 60%

Team Morale

  • Manual Follow-ups↓ 55%
  • After-hours ChasingNear zero
  • Cross-team Clarity↑ Full
5X

First-Year ROI

Return on investment in the first year of full deployment

"

We used to forecast by memory and hope for the best. Now the system looks at three years of our actual orders, accounts for seasonality, and sends the customer a suggested order before they even call us. They confirm on WhatsApp and it goes straight to SAP. We stopped guessing.

person

Operations Director

Leading GCC Frozen Perishable Meat Distributor

Leading GCC Frozen Perishable Meat Distributor (Identity Withheld)

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