The engine at work

Army contract awards

A test build: it goes to no one, and no customer has it. Read 2026-10-25, LEF SI Engine 0.59.0, with no AI model in the read.

The records. 5,000 Army contract award records from USAspending.gov, a public federal source, drawn as a fixed sample of the awards held locally.

What the build does. The engine's own read, with no tool of its own: which combinations of agency, supplier, industry code, place of performance and award type never appear together, each checked against every record.

What the engine found

• The engine read all 5,000 records.
• It looked for pairs of common values that never appear in the same record and found 87.
• The records themselves explain 23 of them. 39 are too thin or too uncertain to stand on, and are leads only. 25 hold in these records.

9 of the engine's checks could not run on these records, each for a reason the run states.

A hospital file, read for a quality director

A test build: it goes to no one, and no customer has it. Read 2026-10-25, LEF SI Engine 0.59.0, with no AI model in the read.

The records. CMS's public Hospital General Information file: 5,419 hospitals, their star ratings, measure groups and footnotes.

What the build does. A peer comparison for each hospital: how its measure groups stand against hospitals of the same ownership, type, emergency services and state, using only the counts and footnotes the file itself publishes, and saying where the file is silent.

From the build’s own read. Footnotes are common in this file: the overall rating carries one for 42.7% of hospitals, and the patient-experience and timeliness groups publish no better-or-worse counts at all, so the brief says so instead of comparing them.

What the engine found

• The engine read all 5,419 records.
• It looked for pairs of common values that never appear in the same record and found 1,282.
• The records themselves explain 823 of them. 8 are too thin or too uncertain to stand on, and are leads only. 451 hold in these records (9 of those are the same gap told again through a field carrying the same information, so 442 distinct).

16 of the engine's checks could not run on these records, each for a reason the run states.

Hazardous materials incidents

A test build: it goes to no one, and no customer has it. Read 2026-10-25, LEF SI Engine 0.59.0, with no AI model in the read.

The records. 1,500 rows of PHMSA's hazardous materials incident reports for 2022 (PHMSA is the federal pipeline and hazardous materials safety agency); they cover 1,464 reports, because one report can take more than one row.

What the build does. An atlas of which ways of shipping (mode, hazard class, packaging) go with injuries or fatalities in these reports, and an inventory of which of the report form's fields are ever filled.

From the build’s own read. Of the 1,464 reports from 2022, 31 distinct dates, the configuration with the most reports of injury or fatality is Highway / class 8 / (not recorded): 2 with an injury, 0 with a fatality, of 25 reports. These are counts in these records, not rates.

What the engine found

• The engine read all 1,500 records.
• It looked for pairs of common values that never appear in the same record and found 5,107.
• The records themselves explain 1,981 of them. 2,661 are too thin or too uncertain to stand on, and are leads only. 465 hold in these records (34 of those are the same gap told again through a field carrying the same information, so 431 distinct).

13 of the engine's checks could not run on these records, each for a reason the run states.