Sage Intacct tags every transaction with dimensions rather than burying detail in a long segmented account code. The standard set covers location, department, project, class, customer, vendor, employee and item, alongside any custom dimensions a company defines. The standard set covers most needs, but businesses are specific, and Sage Intacct anticipates that with Platform Services: you can add custom dimensions, custom objects and Smart Rules to model the way your business actually works.

The question for an AI layer is whether it can read that custom data as well as the standard fields. A good one can. If a company tracks a custom dimension for a business unit or a funding source, AI should analyse by it the same way it analyses by department.

Dimensions
Custom Objects
Smart Rules
Platform Services
Reporting

Custom dimensions for a specific business

The standard dimensions are a starting point. A grant funded organisation needs a funding source dimension. A franchise needs a franchise dimension. Platform Services let you add these, and they behave like the standard dimensions: on every transaction, sliceable, reportable.

An AI layer that reads dimensions generically reads these too, so analysis by a custom dimension is the same question as analysis by department.

Custom objects and platform data

Beyond dimensions, Platform Services let you add custom objects to hold data the standard model does not. AI can query these objects alongside the ledger, so an answer can combine financial data with the custom context a business tracks.

Standard and custom data on one Sage Intacct surface

Smart Rules and consistency

Smart Rules and Smart Events enforce data quality at entry: a rule that a certain transaction must carry a certain dimension, an event that fires when a condition is met. These keep custom data consistent, and AI can help by flagging where data drifts despite the rules.

A transaction missing a dimension a rule expects.
A custom field populated inconsistently across similar records.
A value that falls outside the expected set for a custom dimension.
A pattern that suggests a rule should exist but does not.

Analysing custom and standard together

The value is combining them. Margin by a custom business unit dimension. Cost by funding source and department. AI analyses custom and standard dimensions in the same question, which is the point of a flexible model. This extends dimensional analysis.

Keeping custom data clean

Custom data is only useful if it is consistent. AI helps by spotting drift and by proposing coding for custom dimensions the same way it does for standard ones, connecting to AI dimension coding. Clean custom data makes the custom analysis trustworthy.

Reading the platform generically

The test of an AI layer on Sage Intacct is whether it reads the model generically or only knows the standard fields. ChatFin reads dimensions, objects and custom fields generically, so it adapts to how a business has extended the platform rather than assuming a fixed shape.

The result

Custom dimensions, objects and Smart Rules let a business model its reality, and AI reads all of it, so the analysis fits the business rather than the other way round. This is why a dimensional platform and an AI layer suit each other.

Analyse Custom and Standard Sage Intacct Data Together

Platform Services let you add custom dimensions, objects and Smart Rules. ChatFin reads and analyses that custom data alongside the standard dimensions, sourced to the transactions.

Book a demo to analyse your own custom model.

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