# Background

AI systems are only as good as the data they learn from. The most valuable inputs are not static datasets, but live signals - what happened, when it happened, and whether the event is trustworthy. Today these signals are spread across online platforms and on-chain activity, fragmented across sources, and increasingly polluted by spam, bots, and synthetic behavior.

Teams building AI, analytics, and automation face the same bottlenecks: \
(1) Inconsistent schemas\
(2)Unclear provenance\
(3)Low reproducibility\
(4)Weak integrity guarantees

Users and partners also need clear consent boundaries for online sources, and auditability for high-stakes use cases.