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.
The top row leads with the 4 numbers that matter most: Ticket volume, CSAT, Avg resolution time, First response time. Each shows a delta versus the prior period so you can see direction at a glance. Below that, 2 trend charts (Ticket volume over time, CSAT trend) show how the headline numbers have moved over time. A breakdown (Tickets by channel) splits the metric by dimension so you can see what's driving the total. A detail table (Support 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.
| Period | Ticket Volume |
|---|---|
| Jan | 1.5K |
| Feb | 1.6K |
| Mar | 2.2K |
| Apr | 1.8K |
| May | 1.9K |
| Jun | 1.9K |
| Jul | 2.7K |
| Aug | 2.8K |
| Sep | 2.5K |
| Oct | 3.1K |
| Nov | 2.9K |
| Dec | 3.0K |
| Period | CSAT |
|---|---|
| Jan | 8474.6% |
| Feb | 8927.5% |
| Mar | 8816.4% |
| Apr | 8985.0% |
| May | 9188.1% |
| Jun | 9070.9% |
| Jul | 9543.7% |
| Aug | 9524.8% |
| Sep | 9594.2% |
| Oct | 9480.5% |
| Nov | 9694.6% |
| Dec | 9389.1% |
| Period | Avg Resolution Time |
|---|---|
| Jan | 10 |
| Feb | 9 |
| Mar | 9 |
| Apr | 8 |
| May | 7 |
| Jun | 8 |
| Jul | 8 |
| Aug | 8 |
| Sep | 7 |
| Oct | 6 |
| Nov | 8 |
| Dec | 7 |
| Period | First Response Time |
|---|---|
| Jan | 2 |
| Feb | 2 |
| Mar | 1 |
| Apr | 1 |
| May | 1 |
| Jun | 1 |
| Jul | 2 |
| Aug | 1 |
| Sep | 2 |
| Oct | 1 |
| Nov | 1 |
| Dec | 1 |
| Period | Ticket Volume |
|---|---|
| Jan | 1.5K |
| Feb | 1.6K |
| Mar | 2.2K |
| Apr | 1.8K |
| May | 1.9K |
| Jun | 1.9K |
| Jul | 2.7K |
| Aug | 2.8K |
| Sep | 2.5K |
| Oct | 3.1K |
| Nov | 2.9K |
| Dec | 3.0K |
| Channel | Ticket Volume |
|---|---|
| Paid Search | 311 |
| Paid Social | 513 |
| Organic | 729 |
| 684 | |
| Referral | 729 |
| Period | CSAT |
|---|---|
| Jan | 8474.6% |
| Feb | 8927.5% |
| Mar | 8816.4% |
| Apr | 8985.0% |
| May | 9188.1% |
| Jun | 9070.9% |
| Jul | 9543.7% |
| Aug | 9524.8% |
| Sep | 9594.2% |
| Oct | 9480.5% |
| Nov | 9694.6% |
| Dec | 9389.1% |
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 |
|---|---|---|---|
| Resolution Rate | — | Tickets Resolved ÷ Ticket Volume | Hubspot, Zendesk |
A hubspot customer success 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.
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.
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From signup to a working dashboard in one sitting. No data team required.
Stripe, your CRM, accounting. Definite syncs and models them automatically.
Pick the numbers that matter or let Fi propose them from your data. Every metric gets one definition, governed in one place.
Describe what you need in plain language. Fi builds the dashboard, and you refine by asking follow-ups.