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Platform Concepts

An overview of the key components that make up CallHQ Voice AI agents and the tasks these agents are capable of handling.

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Voice AI Agent Architecture

CallHQ allows you to create intelligent voice agents that can interact in real time and perform useful post-call actions. A CallHQ agent follows a modular pipeline:

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1. Input Medium

The input method determines how the user interacts with the agent:

• Voice: Via phone call or embedded web widget (microphone input)
• Text: (Coming soon) Typed input via web chat
• Visual: (Coming soon) Upload images or documents as part of the interaction

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2. ASR (Automatic Speech Recognition)

Converts spoken input into text format. This transcription is sent to the LLM for further processing.

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3. LLM (Large Language Model)

The LLM processes the transcribed text and generates a relevant response based on the agent’s instructions, tone, and logic. This response is routed to the output processor.

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4. Output Generator

Depending on the type of conversation:

• For voice: TTS (Text-to-Speech) converts LLM output into natural audio
• For visual or text output: responses may be rendered visually or as plain text (Coming soon)

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5. Output Medium

Delivers the generated output to the user:

• Voice: Played back on a call or in-browser via the web widget
• Text/Visual: (Coming soon) Rendered as chat or rich content

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Tasks After Conversation

CallHQ agents can also be configured to perform additional tasks once the primary conversation ends:

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Post-Call Actions

• Call Summarization
  Automatically summarize the entire conversation for review or CRM logging.

• Information Extraction
  Extract structured fields such as customer name, reason for call, appointment time, etc.

• Function Tools (APIs & Triggers)
  Use function tools to invoke APIs or external actions—e.g., booking a slot, sending a webhook, or updating a database.