Food & Beverage

A food or beverage business lives on thin margins and short shelf lives. Order too much and the surplus becomes write-off within days. Order too little and a chain’s shelf is empty in the holiday week. Around that sit the daily jobs: orders that arrive by WhatsApp and phone after closing, a price list for every customer, small accounts that pay late, and raw materials whose price moves every week. We design and build forecasting, order intake and collections systems for producers and distributors, inside the ERP you already run, with one number agreed up front to judge them by.

Where do the margins leak?#

• Shelf life. Every item has its own. One safety-stock rule for the whole catalog overstocks the fresh lines and understocks the long-life ones.
• The calendar. Demand peaks around the holidays, and the holidays move every year against the civil calendar. A forecast built on “the same month last year” misses them.
• The order desk. Grocers, restaurants and chains send orders by WhatsApp, voice note and email, often in the evening for the morning delivery. Someone types each one into the ERP, checks stock and applies that customer’s price.
• Accounts that fade. A wholesale customer rarely leaves at once. It orders a little less, drops a product family, pays a little later, and the sales report shows it months after the decision was made.
• Inputs. Producers buy grains and oils on markets that move weekly, and when you buy matters as much as what you pay.

Where does AI pay in food and beverage?#

In the decisions you already make every day, with better information:

• Item-level forecasts that know the holiday calendar and the shelf life. They feed a purchasing or production recommendation that the planner accepts or edits.
• Orders read from the message and opened in the ERP. Stock and the customer’s price are checked, and only the unusual orders are left for the order desk.
• A weekly list of accounts that are starting to fade, computed from order lines, so a sales rep calls while the account can still be kept.
• Buy-timing for raw materials: a forecast range for the coming weeks rather than a single number.

All of it works only when the forecast is checked against what actually sold, every month, in the open. A forecast nobody checks is an opinion.

Which of our solutions fit?#

• Orders into your ERP: WhatsApp and email orders resolved against the catalog and the customer’s price, opened in Priority with a confirmation back in the chat.
• Dynamic safety stock per SKU: a safety stock for every item that follows its own demand and lead time, instead of one rule for the catalog.
• Wholesale accounts that are reducing spend: reorder-history signals that flag a fading account while it can still be won back.
• Receivables anomaly detection: customers whose payment behavior is drifting, on a weekly list.
• Commodity buy-timing: a probable range for grain and oil prices, to choose when to buy.
• Unattended retail replenishment: for vending machines, smart coolers and micro-markets, a refill list for each location from what that location sells.

How does an engagement start?#

With one product family, one delivery route or one desk. In a short call we pick the problem that costs the most, often write-offs on a fresh line or the morning order backlog. The fixed-price scoping stage then reads your real history from the ERP, for example sales by item and customer, returns and lead times, and says what that data can support. Holidays with too little history are written down too. One success measure is agreed before anything is built, such as the write-off value on the chosen line against the same holiday weeks last year. Rollout is staged: one line first, and the rest after a full month has run. How we work sets out the stages.