RowBotAI is the leading provider of conversational voice and text messaging for customer content. When you provide RowBotAI with your content, such as Word documents, PDF files, spreadsheets, and web URLs, we will ingest it into our platform. Moments later, utilizing a dial-up telephone line or text messaging application, your users will have the ability to speak with and text to the content with an empathetic and accurate AI call agent.
To complete a production-grade service, RowBotAI engages with a process we call Personalized Conversational Commerce.
Personalization
During the personalization phase, we capture your specific requirements for branding, narrative, voice, focus, use cases, and what topics the AI call agent should and should not address during conversations with users and callers.
This includes a careful review of your documents highlighting which sections are particularly important and where users will spend the most time. Having existing metrics for call center analytics concerning frequently asked questions, first-call completion rates, and customer satisfaction would be most helpful.
This helps RowBotAI build a comprehensive test plan and audit procedures to address quality control and assurance.
Conversational
The conversational element for RowBotAI utilizes a Large Language Model. Currently, we’re deploying with ChatGPT 4.0. However, we could use any Large Language Model depending on specific requirements. At no time is the data provided used to train the Large Language Model, thereby ensuring privacy.
Commerce
During the commerce phase, RowBotAI can incorporate call-to-action items such as surveys, links to other URLs for more information, rewards, offers, coupons, payments, and integration with third-party APIs such as Paychex, and ADP.
For example, a user can have a voice or text conversation with the content and receive an email or SMS text summary. They could then complete a request for the number of days off or the total amount of social security deducted from their paycheck during the last pay period.
In summary, this collaborative approach is designed to dramatically reduce the operational cost of existing support and knowledge centers while providing a 10X increase in user satisfaction.
Comments