What Happens After Go-Live: The Importance of Fine-Tuning Your AI Virtual Agent

what-happens-after-go-live

Whether your company is starting to think about contact center automation, or you’ve just invested in a conversational AI solution, there’s one question you may not have asked – what happens after you deploy the intelligent virtual agent?

The cold, hard truth of conversational AI is that it’s not a ‘set it and forget it’ type of technology; it needs constant fine-tuning to ensure the AI virtual agent performs on par or better than live agents.

Join us for this informative webinar as we discuss life after go-live – because that’s where the real work begins. From monitoring how your customers engage the virtual agent to tailoring the natural language understanding (NLU) engine, you’ll learn best practices for improving virtual agent performance and delivering the most seamless self-service experience possible.

Key Takeaways:

  • The maintenance and continuous optimization required after deployment
  • What happens if you don’t continuously train your AI virtual agent
  • How to make the transition – for your customers and internally – to AI self-service as smooth as possible

Watch This
Webinar

gated_webinar_speaker_brian

Brian Morin

Chief Marketing Officer,
SmartAction

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Helena Chen

Director of Product Marketing,
SmartAction

What Happens After Go-Live: The Importance of Fine-Tuning Your AI Virtual Agent

On-Demand Webinar

Whether your company is starting to think about contact center automation, or you’ve just invested in a conversational AI solution, there’s one question you may not have asked – what happens after you deploy the intelligent virtual agent?

The cold, hard truth of conversational AI is that it’s not a ‘set it and forget it’ type of technology; it needs constant fine-tuning to ensure the AI virtual agent performs on par or better than live agents.

Join us for this informative webinar as we discuss life after go-live – because that’s where the real work begins. From monitoring how your customers engage the virtual agent to tailoring the natural language understanding (NLU) engine, you’ll learn best practices for improving virtual agent performance and delivering the most seamless self-service experience possible.

Key Takeaways:

  • The maintenance and continuous optimization required after deployment
  • What happens if you don’t continuously train your AI virtual agent
  • How to make the transition – for your customers and internally – to AI self-service as smooth as possible
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