3-Create-Agent

Jun 01, 2026 11:50 · 4:03 · English · Whisper Turbo · 2 Munyori

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Lecture Index

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in this video we'll focus on one of the most important parts of ken voice creating an

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ai agent ai agents are the digital representatives

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of your business everything else in the platform builds around them in

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ken voice an ai agent is not just a chatbot or voicebot it is a role

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-based conversational entity that can talk to customers understand

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intent access business knowledge trigger workflows and take

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actions across systems each agent is designed to perform a specific business function

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From the left panel,

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we open the AI Agents section.

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This is where all agents are created,

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managed, and monitored.

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To make a new agent,

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we click on Create New Agent button.

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A module opens,

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which consists of eight steps.

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We start with Agent Basics,

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where we define the identity and purpose of the AI agent.

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Here,

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we give the agent a clear name,

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for example,

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Sales Agent or Support Agent,

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and optionally add an internal description so teams know exactly what this agent is responsible

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for.

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We also select the agent type,

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such as support,

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sales,

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information,

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or a fully custom agent.

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This helps Ken Voice optimize call handling,

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tone, and intent detection from the very beginning.

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Next step is voice and language,

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where we define how the agent sounds to callers.

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We choose the primary language,

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select the AI engine,

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and pick a voice model,

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in this case,

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an Eleven Labs voice.

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Using the controls on the right,

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we can fine -tune speaking style,

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tone, and speech speed.

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making the agent sound formal,

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friendly, or conversational,

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depending on the use case.

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We can preview the voice instantly before moving forward.

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In Knowledge Setup,

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we decide what information this agent is allowed to use during conversations.

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Each agent is connected to one dedicated knowledge base,

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ensuring focused and accurate responses.

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We can attach an existing knowledge base,

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such as FAQs or documentation,

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or create a new one by uploading documents,

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adding Q &A manually,

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or connecting a website for live crawling.

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This ensures the agent always responds using verified,

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business -approved information.

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Now we configure call behavior,

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which defines how the agent manages the call lifecycle.

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We set the opening greeting,

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what the caller hears first,

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and configure fallback messages if the agent doesn't understand the request.

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We also control retry limits,

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silence timeouts,

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and call ending behavior,

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including whether the call should automatically disconnect once the intent is resolved.

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This step ensures calls feel natural,

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controlled,

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and professional.

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In the workflow step,

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we decide what actions should happen during or after a call.

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Here,

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we can attach existing workflows such as CRM,

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contact sync,

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order status checks,

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or post -call email summaries.

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Workflows allow the AI agent to go beyond conversation,

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triggering APIs,

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sending emails,

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updating CRMs,

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or notifying teams automatically.

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If needed,

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we can also create a brand new workflow directly from this step.

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Next are escalation rules,

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which define when the AI should hand off the call to a human.

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We can escalate if the caller explicitly asks for a human,

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if confidence drops below a threshold,

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or if repeated fallback attempts occur.

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We also configure whether the transfer should be warm or cold,

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select the destination number,

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and enforce availability checks during business hours.

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This creates a safety net,

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ensuring high -value or sensitive calls are never mishandled.

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Once escalation is set,

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we assign a phone number to the agent.

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We can select an existing number or instantly purchase a new local or international number directly

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from CanVoice.

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This number becomes the live entry point for customers to reach this specific

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AI agent.

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Finally,

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we reach Test and Activate.

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Before going live,

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CanVoice runs a pre -activation checklist to ensure everything is configured correctly,

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including knowledge,

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escalation rules,

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workflows, and phone assignment.

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Using the voice simulator,

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we can test the agent's responses in real time without consuming call minutes.

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Once validated,

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we activate the agent,

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making it live and ready to handle real customer calls.

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This is how AI agents are created and structured inside Kenvoice.

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In the next video,

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we'll move to the next building block,

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buying and managing phone numbers and how they connect customers to AI agents.

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