The LEF Ai Engine reads multi-source public federal data as structure — voids, cross-corpus gaps, and indications of change — then falsifies its own findings before a human analyst decides. Presence-based search cannot do this: a gap has no document to return.
Findings are readable as:
Prior demonstration runs. Structural landscapes only — not targeting products, not operational decisions. Full set via Sample reports in the header.
Where structure lives in one federal corpus but never another — multi-source weave.
Open landscape PDF → Temporal Velocity & moving gapsIndications of change: emerging silence vs decaying silence across snapshots.
Open landscape PDF → Acquisition / finance USAspending × Census × Congress × FECCross-corpus read of awards, legislation, and finance structure on public data.
Open landscape PDF →Try / evaluate, then Secure Enclave field license. No retail seats. No self-serve subscription.
The invite demo is an unclassified demonstrator in a containerized Google Cloud service — isolated and access-gated, but not an accredited or FedRAMP-authorized boundary. Run unclassified / public data only. An accredited enclave deployment is available as a funded effort.
Unlocks the live showcase (public federal sources, alone or woven).
For TPOCs and program evaluators. Reviewed personally. Enclave inquiries welcome on the same address.
licensing@livingedenframeworks.comOutputs are structural arguments for a human analyst. The engine recommends; it does not author the decision.