Positioning
Beyond classic MDM
Governed knowledge for AI and decisions — vocabulary, rules, agents, and masters.
Learn center
Guides, comparisons, and architecture notes
When EntiHub is the right fit, how it compares to other tools, and how to design a governed knowledge layer for AI and business decisions — including classic MDM.
New to EntiHub?
Start here — then install or book a fit call.
Foundations
Key concepts
What EntiHub is, the lifecycle, and how to plan your first rollout.
Honest fit check
When NOT to use EntiHub
Disqualifiers first — then you know if you should proceed.
Try it
Install on Azure
Self-serve from Marketplace into your subscription. Cancel anytime.
Competitive comparisons
EntiHub vs Informatica
Speed to value, deployment model, and team size fit.
EntiHub vs Reltio
SaaS-first versus in-your-tenant architecture trade-offs.
EntiHub vs Profisee
Governance depth, implementation style, and operations model.
EntiHub vs Semarchy
Model-driven capabilities, integrations, and rollout speed.
EntiHub vs Ataccama
Governance operating model and speed to value.
EntiHub vs Stibo
Governance depth and enterprise operating model fit.
EntiHub vs EnterWorks
Operational simplicity and integration readiness.
Decision guides & architecture
Governed knowledge layer
Positioning beyond classic MDM — rules, decisions, and AI-safe definitions.
Decision Memory in MDM
How reusable decision context reduces operational drift.
Integrations
API, webhooks, loads, and downstream consumption patterns.
Data Loads
SQL-driven source-to-entity onboarding Enterprise
Database platforms
Fabric, Azure SQL, PostgreSQL, Oracle, and MySQL.
Automation and AI
CLI & AI agents
Canonical guide — dedicated commands, --json, CI/CD and agent tool loops.
Why MDM needs AI agents
Short story: same governed surface for people and machines.