Jirav is a mid-market cloud-based financial planning and analysis platform. It connects to accounting systems and produces forecasts, budgets, scenario models, and dashboards. Its strength is future-looking projection built on historical data. The projections are useful for capital planning, hiring plans, and lender presentations. What it does not do is read current operating reality against Minimum Mandatory Profit, size the Working Capital Gap, or produce the Layer Cake diagnostic.
The Two Different Questions
Jirav answers: "What does the business look like in a 12-24 month forecast?"
The Aldebert Diagnostic answers: "Can the business clear MMP at its current operating floor?"
Two different questions. Both matter. Confusing them is where owners lose time and money.
Side by Side
| Jirav | The Aldebert Diagnostic (RTO + MMP + Layer Cake) | |
|---|---|---|
| Primary job | Financial planning, forecasting, and reporting | Current-state operating diagnostic |
| Core question | What will the business look like in 12 to 24 months? | Is the business above its MMP floor today? |
| Time orientation | Forward-looking projection | Current reading with historical context |
| Primary input | Historical financials, driver-based models | 11 proprietary Business Biomarkers |
| Output | Forecasts, budgets, scenarios, dashboards | MMP, Layer Cake, Breakeven, written verdict |
| Uncertainty handling | Scenario modeling with assumptions | Realized numbers with restatement discipline |
| Best use | Forward-looking capital and strategic planning | Diagnostic reading of current operating state |
| Users | CFOs, controllers, FP&A analysts | Owner-operators and their advisors |
What Jirav Does Well
Jirav delivers real value for businesses with genuine forecasting needs. Multi-scenario modeling to test different growth trajectories. Driver-based budgets that connect operational inputs to financial outputs. Consolidated reporting across entities and dimensions. Rolling forecasts that update automatically as new data arrives. For businesses with lenders, boards, or investors who want to see forward projections, Jirav is often the right tool. It handles what QuickBooks reports and Excel spreadsheets both struggle with once complexity crosses a threshold.
What the Aldebert Diagnostic Adds
Jirav forecasts the future. The Aldebert Diagnostic reads the present. Return to Owner asks whether the current-state business is above its MMP floor. If it is not, no amount of forecasting will fix it. The forecast will project the same failure with more precision. The diagnostic identifies the specific gap and produces the pricing, cost, or portfolio move required to close it. Once the current state is known and the gap is being closed, the forecast becomes more valuable because the base case is now defensible rather than aspirational.
The Base Case Test
Every forecast is built on a base case. The base case is usually current-state financials extended forward with growth and cost assumptions applied.
If the current state has not been diagnosed against MMP, the base case is arithmetic on unreliable inputs. Reported EBITDA may include undermarked owner compensation. Reported gross margin may reflect the cascade between intended and delivered. Reported working capital may be short of Required without the shortfall being named.
The forecast built on that base case is precise but not accurate. It projects the same misalignment forward. When the forecast fails to match reality, the owner concludes the forecast was wrong. The forecast was correct arithmetic on wrong inputs.
The Aldebert Diagnostic runs the restatements first. Restated EBITDA. Restated Owner Compensation. Restated MMP. Then the forecast is built on defensible numbers.
How They Work Together
Diagnostic first, then forecast. Run Return to Owner to establish restated current-state numbers. Use Jirav to build forward projections on that base. The forecast becomes more accurate because the inputs are accurate. This is how CFOs at mid-market businesses actually run the sequence. Owner-operated SMBs skipping the diagnostic step end up with precise forecasts of a fantasy.
Frequently Asked Questions
At what revenue level does Jirav make sense?
Typically $3M+ for growth-stage or multi-entity businesses. Below that, spreadsheet-based planning usually suffices. Above $50M, enterprise FP&A tools may be more appropriate.
Can Jirav calculate MMP?
Not natively. Jirav can be configured to compute MMP-adjacent metrics if the analyst builds the model. Most Jirav implementations do not include MMP because it is not standard FP&A doctrine.
Should I use Jirav's forecast to make hiring decisions?
Only after the diagnostic confirms Layer Cake clears with the current state. Jirav forecasts hiring impact well when the base case is accurate. See the hiring explainer.
Does the Aldebert Diagnostic replace Jirav?
No. Different jobs. Diagnostic reads current state. FP&A projects future state. Both are useful when the business has the complexity to justify both layers.