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: Open pipeline, Pipeline coverage, New pipeline, Avg sales cycle. Each shows a delta versus the prior period so you can see direction at a glance. Below that, 2 trend charts (Open pipeline over time, Booked revenue trend) show how the headline numbers have moved over time. A breakdown (New pipeline by stage) splits the metric by dimension so you can see what's driving the total. A detail table (Pipeline 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.
Open pipeline
Data ▾
| Period | Open Pipeline |
|---|---|
| Jan | $6.09M |
| Feb | $7.22M |
| Mar | $6.25M |
| Apr | $7.62M |
| May | $7.19M |
| Jun | $6.93M |
| Jul | $7.46M |
| Aug | $8.98M |
| Sep | $9.19M |
| Oct | $10.17M |
| Nov | $9.92M |
| Dec | $9.16M |
Pipeline coverage
Data ▾
| Period | Pipeline Coverage |
|---|---|
| Jan | 7.6× |
| Feb | 8.7× |
| Mar | 7.2× |
| Apr | 8.5× |
| May | 7.7× |
| Jun | 7.1× |
| Jul | 7.4× |
| Aug | 8.5× |
| Sep | 8.4× |
| Oct | 8.9× |
| Nov | 8.4× |
| Dec | 7.4× |
New pipeline
Data ▾
| Period | New Pipeline |
|---|---|
| Jan | $1.93M |
| Feb | $1.62M |
| Mar | $2.16M |
| Apr | $2.00M |
| May | $2.21M |
| Jun | $2.79M |
| Jul | $2.79M |
| Aug | $3.14M |
| Sep | $2.90M |
| Oct | $2.71M |
| Nov | $3.11M |
| Dec | $3.04M |
Avg sales cycle
Data ▾
| Period | Avg Sales Cycle (days) |
|---|---|
| Jan | 43 |
| Feb | 54 |
| Mar | 49 |
| Apr | 44 |
| May | 41 |
| Jun | 39 |
| Jul | 43 |
| Aug | 38 |
| Sep | 37 |
| Oct | 43 |
| Nov | 42 |
| Dec | 46 |
Open pipeline over time
Data ▾
| Period | Open Pipeline |
|---|---|
| Jan | $6.09M |
| Feb | $7.22M |
| Mar | $6.25M |
| Apr | $7.62M |
| May | $7.19M |
| Jun | $6.93M |
| Jul | $7.46M |
| Aug | $8.98M |
| Sep | $9.19M |
| Oct | $10.17M |
| Nov | $9.92M |
| Dec | $9.16M |
New pipeline by stage
Data ▾
| Stage | New Pipeline |
|---|---|
| Discovery | $503K |
| Evaluation | $836K |
| Proposal | $466K |
| Negotiation | $1.23M |
Booked revenue trend
Data ▾
| Period | Booked Revenue (Closed Won) |
|---|---|
| Jan | $643K |
| Feb | $669K |
| Mar | $843K |
| Apr | $846K |
| May | $837K |
| Jun | $874K |
| Jul | $1.22M |
| Aug | $1.03M |
| Sep | $1.16M |
| Oct | $1.33M |
| Nov | $1.39M |
| Dec | $1.23M |
Pipeline health
- Why did pipeline coverage drop below 3x this month?
- Which Salesforce opportunity owner is creating the most new pipeline, and who went quiet?
- Show me the Salesforce deals that slipped out of this quarter's commit.
- What is coverage if win rate drops to the trailing three-month average?
- Break pipeline out by Salesforce record type instead of stage.
- Trace this month's new pipeline back to the Salesforce opportunities created this period.
- Show coverage against next quarter's target using our Salesforce close-date field.
- Break new pipeline by Salesforce opportunity owner and flag any rep who dropped more than 20%.
- Add stage velocity from Salesforce Change History so I can see where deals are stalling.
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 |
|---|---|---|---|
| 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 |
| Win Rate | The cleanest read on sales effectiveness: the share of decided deals you win, won divided by won-plus-lost. | Won Deals ÷ (Won Deals + Lost Deals) | Salesforce |
| Avg Deal Size | Booked revenue per closed-won deal, the lever between volume and value. | Booked Revenue (Closed Won) ÷ Won Deals | Salesforce |
Have our agent watch for you
A salesforce pipeline 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 salesforce pipeline 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.