Describe your dashboard. Fi builds it.
Fi is the AI agent inside Definite. Tell it what you’re trying to understand, and it connects your sources, defines the metrics, and builds the dashboard. One conversation, not a project.
Here’s what’s in it
The top row leads with the 4 numbers that matter most: ARR, Pipeline coverage, Net revenue retention, Gross margin. Each shows a delta versus the prior period so you can see direction at a glance. Below that, 2 trend charts (ARR over time, Net revenue retention trend) show how the headline numbers have moved over time. A breakdown (Revenue by product) splits the metric by dimension so you can see what's driving the total. A detail table (Business health) rounds it out with the secondary metrics and their deltas. Every number is computed from the exact formulas shown in the metric table below. Composites are derived from their components, not pasted in, so the KPI tiles, breakdowns, and totals all reconcile to each other.
ARR
Data ▾
| Period | ARR |
|---|---|
| Jan | $6.95M |
| Feb | $7.39M |
| Mar | $7.91M |
| Apr | $8.56M |
| May | $9.19M |
| Jun | $10.00M |
| Jul | $10.65M |
| Aug | $11.50M |
| Sep | $12.33M |
| Oct | $13.24M |
| Nov | $14.47M |
| Dec | $15.45M |
Pipeline coverage
Data ▾
| Period | Pipeline Coverage |
|---|---|
| Jan | 8.6× |
| Feb | 8.2× |
| Mar | 8.2× |
| Apr | 8.1× |
| May | 8.6× |
| Jun | 7.6× |
| Jul | 7.6× |
| Aug | 8.2× |
| Sep | 8.6× |
| Oct | 7.3× |
| Nov | 8.1× |
| Dec | 7.3× |
Net revenue retention
Data ▾
| Period | Net Revenue Retention |
|---|---|
| Jan | 99.9% |
| Feb | 100.3% |
| Mar | 100.0% |
| Apr | 100.5% |
| May | 100.6% |
| Jun | 100.9% |
| Jul | 100.0% |
| Aug | 101.0% |
| Sep | 100.5% |
| Oct | 100.6% |
| Nov | 101.9% |
| Dec | 100.9% |
Gross margin
Data ▾
| Period | Gross Margin |
|---|---|
| Jan | 81.4% |
| Feb | 79.2% |
| Mar | 80.4% |
| Apr | 81.6% |
| May | 81.0% |
| Jun | 80.4% |
| Jul | 79.3% |
| Aug | 79.8% |
| Sep | 76.9% |
| Oct | 79.5% |
| Nov | 80.2% |
| Dec | 83.0% |
ARR over time
Data ▾
| Period | ARR |
|---|---|
| Jan | $6.95M |
| Feb | $7.39M |
| Mar | $7.91M |
| Apr | $8.56M |
| May | $9.19M |
| Jun | $10.00M |
| Jul | $10.65M |
| Aug | $11.50M |
| Sep | $12.33M |
| Oct | $13.24M |
| Nov | $14.47M |
| Dec | $15.45M |
Revenue by product
Data ▾
| Product | Gross Revenue |
|---|---|
| Platform | $312K |
| Add-ons | $541K |
| Services | $366K |
Net revenue retention trend
Data ▾
| Period | Net Revenue Retention |
|---|---|
| Jan | 99.9% |
| Feb | 100.3% |
| Mar | 100.0% |
| Apr | 100.5% |
| May | 100.6% |
| Jun | 100.9% |
| Jul | 100.0% |
| Aug | 101.0% |
| Sep | 100.5% |
| Oct | 100.6% |
| Nov | 101.9% |
| Dec | 100.9% |
Business health
- Why did NRR drop last quarter when ARR was still growing?
- What is pipeline coverage against next quarter's target?
- Show me the three segments driving the most ARR growth.
- What would ARR look like if churn stays at this rate for the next two quarters?
- Break gross margin out by product line.
- Trace this month's ARR back to the billing subscriptions.
- Add a revenue waterfall showing new, expansion, contraction, and churn MRR.
- Break ARR by segment so I can see where the growth is coming from.
- Show me LTV:CAC alongside retention to see if growth is efficient.
Every metric traces back to your systems
This is the part a BI tool can’t fake. Each metric is defined once, in your warehouse, from a specific object in a specific source. Change the definition in one place and every tile, report, and answer moves with it. So the number on the screen is the number in the source.
| Metric | What it measures | How it's calculated | Sources |
|---|---|---|---|
| ARR | Your monthly recurring revenue annualized, the figure a board or investor anchors on. | MRR × 12 | Stripe |
| Pipeline Coverage | The early-warning gauge on the forecast: how many times your open pipeline covers the quota you have to hit. | Open Pipeline ÷ Quota | Salesforce, Hubspot |
| Net Revenue Retention | The clearest read on whether the product keeps earning its price: how much revenue this year's cohort of customers is worth versus last year, after expansion, contraction, and churn net out. | (prior MRR + Expansion MRR − Contraction MRR − Churned MRR) ÷ prior MRR | Stripe |
| Gross Margin | The share of net revenue left after the direct cost of delivering the product, the ceiling on how efficiently the business can grow. | (Net Revenue − COGS) ÷ Net Revenue | Stripe, Quickbooks |
| LTV : CAC | The payback test on growth spend. Lifetime value divided by acquisition cost. | LTV ÷ CAC | Stripe, Quickbooks |
| Customers | The count of active paying customers at the end of the month, after new logos and churn. | prior Customers + New Customers − Churned Customers | Stripe |
Have our agent watch for you
A executive dashboard tells you what happened, and Fi tells you why. The last step is not having to remember to check. Point Definite at the one number you can’t afford to miss, and it watches that number for you off the same definitions as your dashboard. When it moves, you hear about it before the next review instead of during it. One metric, one action, always reversible.
Built from whatever you already run on
Connect the systems you already use. Any source of these types works, and you don’t move data into a warehouse, because Definite is the warehouse.
No warehouse to stand up or connect. See how the platform models your data →
Build your executive dashboard
From signup to a working dashboard in one sitting. No data team required.
Connect your sources
Stripe, your CRM, accounting. Definite syncs and models them automatically.
Decide your metrics
Pick the numbers that matter or let Fi propose them from your data. Every metric gets one definition, governed in one place.
Ask Fi to build it
Describe what you need in plain language. Fi builds the dashboard, and you refine by asking follow-ups.