What is a semantic data model?

A semantic data model organizes data around what each piece of information means and how it relates to other information, rather than around how it is stored.

In accounting, a semantic data model connects financial activity to objects such as vendors, customers, accounts, departments, and transactions instead of treating each transaction as an isolated row of text. These relationships give AI the context it needs to understand financial activity rather than relying only on transaction descriptions or exact text matches.

Traditional accounting systems often store transactions as text rows in relational tables. In an AI-native ledger, vendors, customers, categories, and transactions exist as objects the system can relate to each other. This allows the system to recognize that different transaction descriptions refer to the same vendor, or that two vendors are similar enough for their accounting history to provide useful context. The result is a system that can understand the meaning and relationships within financial data, not just store it.

Related terms: Financial object, Accounting context, AI-native accounting, Agentic General Ledger™ (AGL®), Ledger-native