> ## Documentation Index
> Fetch the complete documentation index at: https://docs.flokitai.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Core concepts

> The operating model behind FloKit.AI.

## Growth loop

The growth loop is the connected path from acquisition through retained value:

```mermaid theme={null}
flowchart LR
  Channels["Channels"] --> Creatives["Creatives"]
  Creatives --> Funnel["Web-to-app and onboarding"]
  Funnel --> Paywall["Paywall and offers"]
  Paywall --> Revenue["Revenue"]
  Revenue --> Retention["Retention and LTV"]
  Retention --> Actions["Growth actions"]
  Actions --> Channels
```

## Cohort quality

FloKit compares cohorts by downstream outcomes, not only top-of-funnel cost. A cohort can look efficient on CAC and still be weak if trial conversion, retention, or paid renewal quality drops.

## Payback window

The payback window is the time horizon used to compare acquisition spend against revenue and retained value. Teams usually start with a default window, then tune it by category, country, product, and cash constraints.

## Guardrails

Guardrails are the limits that keep agentic growth operations controlled. They include spend caps, excluded campaigns, action approval rules, revenue thresholds, and rollback policies.

## Action queue

The action queue is where FloKit turns signals into proposed moves. Examples include shifting budget, pausing low-quality creative, scaling a stronger cohort, or opening a paywall test.