Nonprofit finance teams need two layers: a fund accounting system that records what happened, and a planning platform that models what happens next. Abacum is the AI-native business planning platform for scaling enterprises. It brings all your data, business logic and business context into one governed place. We plan; we are not a fund accounting system. This guide shows which tools belong in each layer and how to compare them. Funding is harder to predict, and 36% of nonprofits ended 2024 with an operating deficit (Nonprofit Finance Fund, 2025 State of the Sector).
Two layers, two jobs
Layer | Job | Typical tools |
|---|---|---|
Fund accounting and ERP | Record gifts, grants and restricted funds; close the books | Sage Intacct and other nonprofit accounting systems |
Budgeting and forecasting | Build budgets, forecast, run funding scenarios, report to the board | Abacum, Budgyt, PlanGuru, Pigment, Anaplan, Workday Adaptive Planning, Jirav, Cube |
Spreadsheets | Flexible one-off analysis | Excel, Google Sheets |
If a tool is described as a "financial planning tool" but only records transactions, it sits in the first layer. Make sure you cover both.
What to look for in a nonprofit planning tool
A plan for every funding scenario. Model a grant renewed, cut or delayed and see the impact before the board asks.
Program budgets that roll up. Every program and grant ties to one organization-wide picture.
Budget ownership across departments. Program and department leads build their own budgets with version control and approvals, while finance keeps control.
Board reporting without the month-end scramble. Commentary is drafted for you and finance approves every number.
A connection to your accounting system. Actuals flow in from the ledger, which stays the system of record.
The tools compared
Tool | Approach | Confirm in a demo |
|---|---|---|
Abacum | AI-native business planning platform on one governed layer of data, logic and context | Funding scenarios, program roll-ups and board reporting on one model |
Budgyt | Budgeting software with a nonprofit focus | How forecasting and scenarios are handled |
PlanGuru | Budgeting and forecasting software with a page for nonprofits | How approvals and multiple contributors work |
Sage Intacct | Cloud accounting suite used as a system of record | How it connects to a separate planning layer |
Pigment | Flexible modeling platform for teams willing to build and maintain their own planning models | Who owns the model after go-live |
Anaplan | Multi-dimensional planning for large, complex models | Who builds and maintains the models |
Workday Adaptive Planning | Planning connected to the Workday suite | Fit if your finance and HR systems already run on Workday |
Jirav | Dashboards and planning connected to accounting systems | How program-level budgets roll up |
Cube | Planning that runs on Excel or Google Sheets | How versions reconcile across budget owners |
Pigment is a flexible modeling platform for teams willing to build and maintain their own planning models. Your team or an implementation partner designs it and keeps it running, so confirm who will own the model after go-live.
How Abacum supports nonprofit planning
Funding scenarios. Model a grant renewed, cut or delayed on the live plan.
Program budgets that roll up to one organization-wide view.
Replace the 30-tab spreadsheet nobody else can edit. Program and department leads plan in their own spaces, and finance owns the approvals.
Board packs without the scramble. Agents draft the commentary, and finance approves every number. Agents propose, the planning engine calculates, and finance approves every change to reported figures.
Models by description. With AI Modeler, describe what you need in plain language, or bring the spreadsheet you already built, and get a working model in minutes. Nothing saves until you approve. It is included with the platform, with no credits and no meter.
Spreadsheet-friendly. Import a budget or forecast as a version and export platform work to a spreadsheet in Excel or Google Sheets.
Implementation runs six to nine weeks depending on data complexity, entity count and workflows.
