Sources
Where data originates: public feeds, internal records, repositories, APIs, reports, or structured datasets.
The methodology page for SEAMS explains the structure, reasoning model, and technical foundation behind the platform.
SEAMS starts from a simple premise: systems should be observed before they are resolved. In complex environments, forced early convergence often hides the conditions that matter most.
Where data originates: public feeds, internal records, repositories, APIs, reports, or structured datasets.
How content is classified, grouped, and made comparable across runs and domains.
How a run is defined: which sources, which buckets, which settings, and what kind of output is expected.
How structure and consistency are checked without pretending uncertainty has disappeared.