You want to automate auto insurance conversations with a bot that can help customers with transactions such as making premium payments and filing claims. You are an insurance company with a contact center providing customer support to auto, home, and life insurance policy holders. You are charged for the 300 minutes of training time at $0.50 per minute, leading to total training charges of $150.00 for a month for the 180K lines of transcripts. The automated chatbot designer takes about 5 hours (or 300 minutes) to analyze the conversation transcripts and surface the design. Let’s assume that the calls handled by the top tier agents over a month generate 180K lines of transcripts (assume your contact center has 100 agents, you pick the top 10 high performing agents each answering 20 calls/day assuming 30 lines of transcript per call, you will have 6K lines daily or 180K lines monthly). You select the conversation transcripts from customer calls handled by your high performing agents as an input to the automated chatbot designer to create a high-quality bot design. You want create a bot to augment your contact center operations and improve efficiencies. You are a regional credit union and operate a contact center to help customers with queries and transactions related to their bank accounts.
#Alexa speech to text api pricingf for free
From the date you get started with Amazon Lex, you can process up to 10,000 text requests and 5,000 speech requests or speech intervals per month for free for the first year. You can also use Automated chatbot designer for two hours of training time per month for first two months. Let me know once you are ready.” The request and response model is a different user experience where a user input is required as an initiator. For example, you can configure the bot to keep a conversation going when the user needs more time to respond by sending periodic messages such as “Take your time. With streaming conversation, the bot continuously listens and can be designed to respond proactively. Pricing for Amazon Lex is based upon these two interaction models. In a streaming conversation, all user inputs across multiple turns are processed in one streaming API call.
With the request and response interaction, each user input (voice or text) is processed as a separate API call. Amazon Lex bots are designed for a request and response interaction or a continuous streaming conversation. There is no upfront commitment or minimum fee. With Amazon Lex, you pay only for what you use. Amazon Lex is a service for building conversational interfaces into any application using voice and text.
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