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Documentation Index

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Build conversational AI assistants for customers, agents, and employees across voice and digital channels. Automation AI uses DialogGPT and AI Agents to deliver multi-turn conversations that understand intent, retain context, and respond naturally.

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Key Components

┌──────────────────────────────────────────────────────┐ │ Automation AI │ └───────────────────────────┬──────────────────────────┘ │ │ │ ┌────────────────┼────────────────┐ │ ▼ ▼ ▼ │ ┌─────────────┐ ┌─────────────┐ ┌──────────────┐ │ │ DialogGPT │ │Agent Flows │ │ AI Agents │ │ │─────────────│ │─────────────│ │──────────────│ │ │ Agentic │ │ Dialog Task │ │ Tool-Calling │ │ │orchestration│ │ + │ │ + │ │ │ No training│ │ Agent Nodes │ │ External │ │ │ data needed│ │ │ │ Integrations │ │ └──────┬──────┘ └──────┬──────┘ └──────┬───────┘ │ └────────────────┼────────────────┘ │ │ │ ┌────────────────┴────────────────┐ │ ▼ ▼ │ ┌──────────────────┐ ┌──────────────────┐ │ │ Conversation │ │ Evaluation │ │ │ Management │ │──────────────────│ │ │──────────────────│ │ Testing Suite │ │ │ Interruptions │ │ Validate flows │ │ │ Clarifications │ │ Pre-deployment │ │ │ Context Switches │ │ checks │ │ └──────────────────┘ └──────────────────┘
ComponentDescription
DialogGPTAgentic orchestration engine that routes conversations using generative models—no training data required.
Agent FlowsConversational workflows combining and Agent Nodes for goal-driven service interactions.
AI AgentsAgent Nodes with tool-calling that handle complex tasks via contextual intelligence and external integrations.
Conversation ManagementHandles interruptions, clarifications, and context switches mid-conversation.
EvaluationTesting suite to validate conversational workflows before deployment.

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DialogGPT Orchestration

DialogGPT analyzes each user message and routes it to the appropriate handler:
┌─────────────────────────────────────────────────────────┐ │ User Message │ └──────────────────────────┬──────────────────────────────┘ │ ▼ ┌─────────────────────────────────────────────────────────┐ │ DialogGPT Orchestrator │ │ │ │ Analyzes intent, context, and confidence to route to: │ │ │ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ │ │ Agent │ │ Generative │ │ Agent │ │ │ │ Flows │ │ AI │ │ Handoff │ │ │ │ │ │ │ │ │ │ │ │ Structured │ │ LLM-powered │ │ Transfer │ │ │ │ tasks │ │ │ │ to human │ │ │ └─────────────┘ └─────────────┘ └─────────────┘ │ └─────────────────────────────────────────────────────────┘

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Build an AI Agent

Follow these steps to create, configure, test, and deploy an AI Agent.

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1. Create and Configure the App

StepWhat to do
Create the appCreate a DialogGPT-based app. The platform auto-enables the required XO GPT models; Dialogs and FAQs are on by default. Guided Onboarding →
Configure DialogGPTDefine Conversation Types and set models for Chunk Shortlisting and Conversation Orchestration. Enable or disable Intent and Conversation Events and override defaults as needed. Conversation Orchestration →

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2. Configure Generative AI

StepWhat to do
Integrate an LLMConnect to a supported LLM provider, a bring-your-own model, or Kore.ai XO GPT. For Tool Calling, Streaming Responses, or Dynamic Variables, use a custom prompt with a pre-built or custom integration. LLM Integration →
Create a custom promptTailor model behavior per use case—build from scratch or import an existing prompt. Agent Node supports tool calling and prompt streaming with OpenAI/Azure OpenAI response formats in custom JavaScript V2 prompts. Prompts Library →
Enable GenAI featuresActivate LLM-powered features that accelerate development and improve runtime performance. Features must be explicitly enabled before use. GenAI Features →
Configure data safeguardsEnable PII/sensitive data anonymization at the assistant and LLM level. Data Anonymization →
Set up Guardrails to enforce appropriate AI outputs. Guardrails →

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3. Build Flows and Connect Knowledge

StepWhat to do
Create a DialogDefine conversation flows using interlinked nodes. Nodes retrieve data, perform actions, call external apps, send messages, and control branching logic. Dialog Tasks →
Add an Agent NodeUse LLMs and tool calling to handle complex tasks, collect entities, and integrate with external systems. Supports multilingual conversations and contextual intelligence. Agent Node →
Connect Search AIIndex content from websites, documents (PDF, Office), and third-party systems (ServiceNow, Confluence, etc.) to give DialogGPT a reliable knowledge base. Content Sources →
Add supporting nodesUse Prompt, Entity, and Agent Transfer nodes with transitions to complete the conversation flow. Nodes Overview →

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4. Test

StepWhat to do
Interactive testingValidate your app in real time using the built-in Playground before publishing. Playground →
Batch testingUpload CSV or JSON test cases to validate accuracy and reliability at scale. Generates comprehensive performance metrics. Batch Testing →

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5. Deploy

StepWhat to do
Enable a channelConnect the agent to one or more voice or digital channels. The agent isn’t accessible to users until at least one channel is enabled. Digital Channels →
Configure agent transferSet up to a human agent. Integrations are platform-hosted—no custom BotKit required. Agent Transfer →
PublishSubmit the app through the publishing flow for admin review before making it available to end users. Publishing →