Government & public sector
Build a shared operational picture without hiding uncertainty.
Bring together official feeds, operational reports and human observations. Keep source origin visible, identify gaps, connect signals to critical functions and assign uncertain questions for verification.
A typical scenario
Severe weather affects a region. Warnings arrive from official feeds, field reports arrive from operational staff, and a utility reports a disruption. Each arrives separately, at a different time, with a different level of confidence. SKALV holds them as evidence with their origins intact and shows what they collectively support.
Evidence and source health
Official feeds are bound to named sources, so an operator can see which sources are reporting, which are delayed and which have gone quiet — before the quiet source is mistaken for an all-clear.
Critical functions as nodes
Care facilities, water supply, schools, transport links and communications can be modelled as nodes with dependencies between them. A signal then produces a list of possibly exposed functions rather than a general regional warning.
Verification with a named owner
Where the evidence does not settle a question, a verification task goes to a specific person with a specific question. The answer is recorded as evidence and can change the assessment in either direction.
Auditability for the review afterwards
Every assessment, verification and administrative change is recorded with actor and time in an append-only trail, so a post-event review can reconstruct what was known, when, and on what basis.
See SKALV with your own operational scenario.
Bring a real scenario — the sources you follow, the functions you cannot lose — and we will show where SKALV fits and where it does not.