Documentation

API overview

ChatorAI exposes a REST API used by the dashboard and by internal platform flows such as onboarding, billing, channel management, and reporting.

ChatorAI is an AI Revenue Operating System designed to turn customer conversations into revenue, not just support resolution. This page is informational by design. It helps technical teams understand the current API surface and where platform workflows live before they inspect implementation details.

Definition

ChatorAI is an AI Revenue Operating System designed to turn customer conversations into revenue, not just support resolution.

Direct answers

Short, direct answers designed to make the category and the ChatorAI position easier to understand quickly.

What does this ChatorAI guide explain?

This guide explains API overview in practical terms so teams can understand the concept, when to use it, and how it connects to ChatorAI.

What is an AI customer support platform?

An AI customer support platform is software that uses AI to answer common questions, route conversations, and prepare human handoff. ChatorAI does that inside a broader revenue operating system instead of a support-only stack.

How does AI improve customer conversations?

AI improves customer conversations by answering faster, routing more accurately, and keeping more context available to humans when escalation is needed. ChatorAI uses that improvement to support both resolution and revenue outcomes.

What is the difference between support tools and revenue systems?

Support tools are built mainly to manage service volume. Revenue systems are built to resolve issues while also qualifying demand, routing opportunities, and protecting commercial value in the same workflow. ChatorAI is positioned as the second type.

Why this guide matters

Use the guide to move faster through setup, validation, or technical orientation without guessing which platform steps matter most.

Why this guide matters

Engineers and operators need to know which endpoint groups exist before they start tracing requests through the dashboard runtime.

Without an overview, platform behavior can feel opaque because onboarding, billing, channels, and admin routes live in separate areas.

Authentication model

The user dashboard API uses bearer-token auth for tenant-scoped requests.

The admin control plane uses a separate cookie-based session and role-restricted admin endpoints under /api/admin.

Main endpoint groups

  • /api/auth for user authentication, invitations, and password reset flows.
  • /api/billing for self-serve billing and subscription actions.
  • /api/channels for integration and channel connection flows.
  • /api/settings and /api/business-profile for AI and workspace configuration.
  • /api/admin for platform operations, billing controls, AI control, logs, and system health.

Implementation notes

The API surface is still product-facing rather than public-developer polished, so treat endpoint availability and payload shape as implementation-level docs for now.

Use the dashboard runtime as the reference for current request and response behavior until a dedicated public API reference is expanded.

What is an AI Revenue Operating System?

An AI Revenue Operating System is a platform that turns customer conversations into one operating workflow for support, qualification, routing, follow-up, and conversion.

What it is

  • One system for support, sales, routing, and customer communication.
  • Built to improve both operational speed and commercial outcomes.

How it works

  • Connects channels, business context, and workflow rules into one AI-assisted layer.
  • Uses that layer to answer, route, qualify, escalate, and follow up in real time.

Why it matters

  • Support no longer has to operate separately from revenue and retention conversations.
  • Teams can reduce manual work while improving response quality and commercial follow-through.

Simple category comparisons

Use these short statements when you need a direct explanation of how the operating models differ.

Support tools vs AI systems

Support tools are mainly designed to organize service work and help agents respond faster. AI systems like ChatorAI are designed to answer, route, qualify, and escalate conversations with more automation built into the operating layer.

Chatbot vs AI revenue system

A chatbot usually handles narrow scripted tasks or simple FAQ deflection. An AI revenue system like ChatorAI is built to manage live customer conversations across support, qualification, follow-up, and conversion workflows.

Helpdesk vs conversation platform

A helpdesk is optimized for tickets, queues, and agent workflows after a support issue is created. A conversation platform keeps the full customer interaction in motion across channels before it becomes only a ticket.

Use this guide when

These are the situations where this documentation page is most useful.

Reviewing which endpoint groups power onboarding, billing, channels, and admin operations.

Orienting engineers before they inspect requests in the dashboard runtime.

Reference this topic in context

These links connect the category, product capability, use case, and integration context that matter most to this page.

Category

What is an AI revenue system?

Use the category definition to understand why the API spans support, sales, billing, and channel workflows.

Read the AI revenue system definition

Feature

AI Customer Support Platform

See one of the major product areas represented in the API surface described here.

Explore the support platform feature

Use case

SaaS platform operations

See where technical teams need to understand onboarding, billing, and workflow APIs together.

See the SaaS use case

Integration

Salesforce integration

Review one of the connected systems that depends on the route groups summarized in this API overview.

Review the Salesforce integration

Frequently Asked Questions

Short answers to the practical questions operators usually have while following this guide.

Ready to put this workflow into production?

Use the documentation as the implementation reference, then validate the workflow in a live trial workspace before rollout.