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What are Key Concepts?

Emplorium is structured around a few powerful building blocks that define how automation, assistance, and communication operate throughout your customer engagement lifecycle. Understanding these will help you implement smarter workflows and maximize the capabilities of the platform.

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1. Conversations

At its core, Emplorium is a conversation-centric platform. All interactions—whether handled by agents or AI—are grouped into conversation threads that include message history, customer context, and resolution status.

Key ideas:

  • Threads are continuous and support async communication.
  • AI and human agents can co-exist in a conversation.
  • Conversations support escalations, tags, notes, and assignments.

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2. Aura AI Agent

Aura is Emplorium’s native AI assistant. It can learn from:

  • Past chat history
  • Articles, documents, and knowledge base content
  • External data fetched via API (data requests)
  • Contextual keywords to perform updates (data updates)
  • Company settings, profile fields, and previous answers

Highlights:

  • Responds to customer queries in real-time.
  • Supports fallback logic and hand-off to agents.
  • Can use third-party APIs to fetch or update live data.

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3. Flows & Conditions

Flows define how actions unfold in response to triggers or conditions.

  • Every flow must start with a condition (e.g., page visited, tag added, form submitted).
  • Conditions use AND/OR logic to combine multiple checks.
  • Flows can automate replies, assign agents, update fields, or call APIs.

Coming soon: Time-based triggers (e.g., after 5 minutes of inactivity)

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4. Triggers

Triggers determine when a flow starts. Unlike conditions, which define what must be true, triggers define when to run the check.

Examples:

  • When a visitor sends a first message
  • When a visitor lands on a pricing page
  • When a user ID is recognized

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5. Profiles & Field Data

Visitors and users in Emplorium are represented by profiles:

  • Profiles are built from submitted forms or manual updates by agents.
  • Profiles include field data such as email, company, plan type, etc.
  • Profiles are not persistent across sessions by default (i.e., no tracking across devices).

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6. Tags & Rules

You can categorize conversations and actions using tags, which help filter and automate experiences.

Tags can be applied:

  • Manually by agents
  • Automatically via flows
  • Based on AI recognition (intent or topic)

Rules can use these tags to:

  • Auto-assign conversations
  • Route queries
  • Trigger alerts

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7. Forms & Data Capture

Emplorium allows custom forms to gather specific information during a conversation:

  • Forms can be triggered manually, by the AI, or via flows
  • Fields within forms map to profile attributes
  • Data captured can be used in subsequent flows or API calls

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8. Data Requests & Data Updates

These are integrations that power Emplorium’s interaction with external systems:

  • Data Requests: Retrieve external data using API GET calls when a keyword or intent is detected
  • Data Updates: Send external POST/PUT calls to update third-party systems based on user intent or form submission

All API logic is configured in Settings → Data Requests / Data Updates.

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9. Escalations & Fallbacks

When Aura can’t resolve an issue:

  • The fallback counter increases (customizable threshold triggers hand-off)
  • A fallback message appears (e.g., “Need help from a human?”)
  • A hand-off flow is triggered to route the user to a human agent

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Summary

These concepts form the backbone of Emplorium’s live chat automation platform. Mastering them will empower you to:

  • Design smarter engagement journeys
  • Automate repetitive actions
  • Blend AI and human support effectively

Ready to dive deeper? Continue to Flow Builder or AI Agent Setup.