Demonstration · Illustrative data · BI Consulting Services
AgriGlobal Market × BI Consulting Services

Trade Intelligence Suite
prices · lanes · counterparties · margin

A multi-dashboard Power BI suite fed by API sources — customs trade data, commodity price feeds, ERP contracts and carrier tracking — covering the rendering, oilseed, vegetable-oil, meat and grain trade that AgriGlobal Market tracks across +70 countries.

Prepared for Felipe AgriGlobal Market · Miami, FL
September 2026
Demonstration · Illustrative data
Commodity group
Destination
Period

Trade lanes — origin port → destination port

Pacific-centred so the Callao→Shanghai and Rosario→Ho Chi Minh routes read as sailed. Arc width = tonnes in period; colour = commodity group. Hover a lane.

What this board answers

Three questions a trading director asks on a Monday morning.

FOB price index — trailing 12 months

Volume-weighted, indexed to the first month = 100 so groups with different US$/t can share one axis. Selected period shaded.

Shipped volume by commodity group

Tonnes per month, stacked by group. Selected period shaded.

Margin by commodity

Gross margin % on landed trades (CIF − FOB − freight − finance), period vs prior period.

Supplier & buyer performance

On-time arrival, quality claims and days-to-pay, ranked by tonnes in period.

CounterpartyRoleTonnesOn-timeClaimsDays to pay

Ask the data

Natural-language layer over the same model. The answer below is generated from the current filter selection — try changing a filter.

Other questions this layer answers
Which buyer's payment days worsened most this quarter? Show FOB vs CIF spread on soybean oil to Mumbai Alert me when fish meal FOB moves more than 4% week-on-week Which lanes have freight above 9% of trade value? Compare Rosario draft delays to on-time arrivals

API feeds behind the suite

"Multiple dashboards using an API for the sources of information" — each source lands in one model, refreshed on its own schedule.

Demonstration · Illustrative data · BI Consulting Services
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Private AI on your own server

The "ask the data" ideas on this board are designed to run on a GPU server inside your own network — an open-weight model over your own documents, cited answers, no per-seat licence, nothing leaving the building. The short deck below explains how it works. Scroll through, or download it as a PDF.

Private AI Servers — slide 1 of 14
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