| Can be expensive and complicated to develop. |
Quicker and cheaper to develop and launch. |
| Capable of voice and text input and output. |
Capable of text only inputs and outputs. |
| Can be deployed on websites as voice assistants, etc. |
Can be used as a chat interface only. |
| Can automatically resolve vast majority of user inquiries and provide tailored responses to customers. |
Able to deliver responses based on trained conversation patterns / keywords, quickly and accurately but can’t answer questions / queries outside of the trained set. |
| Detects intent and sentiment in user. |
Any updates to pre-defined rules and conversational flow demands reconfiguration, manual maintenance & updates – difficult and time-consuming to scale. |
| Easy deployment and integration with existing databases. |
Not advanced enough to integrate with existing databases. |
- Highly scalable – as the company’s database updates, so does the Al interface.
- Can save complex customer data such as purchasing history, browsing habits and demographic information.
- Ongoing improvement – learns from every interaction and GPT update. Learning customer conversations and continually getting smarter.
- Multiple language capability.
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