SAMPLE: Ceres Global × BI Consulting Services — Grain Merchandising & Operations Board

Grain merchandising & operations board — 13 facilities, 45 million bushels, one warehouse

An executive view built on top of a modelled Ceres data warehouse: bushels handled, storage utilisation by facility, margin by commodity, rail and truck logistics across the Northern Plains and Prairies — plus a live health panel for the warehouse itself. Every panel below recalculates when you change the filters.

Bushels handled by month — receipts vs shipments

Trailing 24 months · million bushels

Receipts (in)Shipments (out)Storage utilisation %Selected period

What this board answers

Three questions from the June 2024 discovery call, answered with numbers from the board.

Facility network — elevators & terminals

Circle = licensed capacity · fill = utilisation

Owned facilityJoint-venture assetRail corridor to port / millUtilisation 40% → 95%

Storage utilisation by facility

Avg. of month-end stock ÷ capacity

Red tick = 90% operating ceiling. Sorted high → low.

Margin by commodity

Gross margin, US$ million · bar length = margin, label = ¢/bu

Share of bushels shipped

Top facility by margin

Rail vs truck shipments

Million bushels / month

Rail (BNSF · CPKC · CN)Truck

Data warehouse health

Live

Sources integrated, refresh status and row volume for the selected slice.

Source	Refresh	Status	Rows

Ask the data

AI layer · natural-language query over the warehouse

A typed question, answered from the same model that drives the board. Shown here as a static example of the AI layer.

“”Enter ↵

Private AI on your own server

The "ask the data" panel above is built to run on a GPU server inside your own network: an open-weight model over your own documents, with every answer citing the file it came from. No per-seat licence, works offline, and nothing leaves the building.

How it sits in your environment

One appliance-class server on your rack or in a secured closet. Your files are indexed where they already live; the model runs locally; answers come back with the source page attached.

What that means in practice

1
Your data only, on your hardwareAn open model over your own documents and exports. No third-party AI processor, no data-transfer agreement to review.
2
Every answer cites its sourceReplies point to the file and page they were drawn from, so people check the answer instead of trusting it blind.
3
No per-seat licenceThe whole team can ask questions. Cost is the server and our build, not a monthly number that grows with headcount.
4
Works offlineIf the internet connection goes down, the answers still come. Nothing depends on a vendor's uptime or pricing changes.