34 tests / 22 source files
A repaired checkpoint recorded 34 local tests across the then-current 22-file source body with direct runtime evidence.
A logistics intelligence engine that interprets event sequences as operational state, produces bounded next-movement predictions, and learns from later outcomes.
The useful question is where the shipment actually is in the operational process, which new event changes that state, what next movement is supported, and how the eventual outcome should revise later predictions.
The engine combines timestamped carrier events, route/stage logic, contradictions, location-specific patterns, delivery-window reasoning and feedback from actual outcomes.
Product development has progressed through local validation, family-boundary testing, hosted CI/artifact custody, container/security checks and repeated public-contract/outcome-feedback hardening.
Each item below is deliberately narrower than a product-readiness or superiority claim.
A repaired checkpoint recorded 34 local tests across the then-current 22-file source body with direct runtime evidence.
The family intake included malformed/forbidden-state cases and import-isolation checks before and after the repair commit.
The post-repair workflow and artifact were inspected at the exact head; artifact content carried provenance, security and container-equivalence evidence.
The inspected validation artifact recorded zero Bandit findings and zero Trivy HIGH/CRITICAL findings for the tested fs/image surfaces, with host/container receipts equal.
It does not claim universal carrier accuracy, production-provider coverage, signed/deployed external runtime completion, automatic learned-rule promotion, empirical multi-address superiority, ROI, or guaranteed delivery times.
Later product work has continued through public-contract and outcome-feedback bridge changes, while the external signed-runtime release spine and production-provider/empirical calibration remain separate held proof classes.