Data flows as the operating layer
Map services across people, AI systems, applications, data, controls, and approval boundaries.
The operating layer for organizations managing AI-enabled service delivery. Map how work moves, prove who owns each step, and connect governance to the way services actually run.
Liquid Learn is built for regulated, high-accountability teams that need more than policy documents and disconnected spreadsheets.
Map services across people, AI systems, applications, data, controls, and approval boundaries.
Show where AI generates, recommends, classifies, or automates work, and where people review or approve it.
Tie obligations, controls, reviews, and evidence to the actual workflow being operated.
Attribute AI usage and spend to the right service, team, business unit, tenant, or customer.
Connect service flows to frameworks such as ISO 42001, NIST AI RMF, and risk-based AI obligations.
Find complexity, review load, cost waste, missing controls, and high-risk workflow patterns.
Turn policies and controls into role-based enablement that supports daily execution.