Busiest airports
Freight handled in the latest month held, with change against the same month a year earlier.
Freight handled in the latest month held, with change against the same month a year earlier.
Total freight carried per airline across all periods held. Industry-wide totals are excluded so carriers are not double-counted.
Monthly freight tonnage with a three-month projection.
Freight is flights multiplied by the tonnes each one carries, so a year’s change splits exactly between the two. They need different responses: more flights needs slots and stands, fuller flights needs handling and warehousing.
Plain-language summary of what the series shows.
Months where observed traffic departed from the seasonal pattern.
How much freight each departure actually lifted, and how much rode alongside each passenger. Volume and intensity are different things: the busiest airport is not always the most cargo-dense.
How evenly freight is spread across airports, month by month.
Whether a carrier’s freight moves with its passenger flying.
Load factor, tonnes lifted per departure, and mail’s share of what was carried.
Predicted freight with an 80% interval: the range the model expects the true value to fall in four times out of five.
Narrated from the flagged figures. Every number is checked against a stored row before publishing; anything that does not resolve is rejected rather than shown.
Questions are mapped onto registered metrics and answered by SQL. The model never calculates a figure: it reads rows it was handed.
Recorded trace, replayed at reading pace.
Retries are the loop recovering.
Per-step policy provenance.
Documents retrieved and facts extracted from each.
Source text indexed so a citation can point at a paragraph, not a whole PDF.
Dense vector similarity and keyword search, fused. Returns the passage, never a computed number.
Last pipeline run, stage by stage, and the counters exposed for monitoring.