Conversational AI can be used to power chatbots to become smarter and more capable. But it's important to understand that not all chatbots are powered by conversational AI.
Basic chatbots only have the capacity to complete a limited number of tasks. Typically, this means answering simple FAQs and not much else. In order to meet the demands of larger enterprises, chatbots need conversational AI to enhance their ability to understand human language and to provide transactional functionality in addition to their informational capabilities.
With conversational AI you can go beyond just translating website content into simple chatbot responses. Instead, customers can block credit cards, file insurance claims, upgrading data plans, scan invoices and much more - directly from the chat window.
Basic chatbots are useful for handling a very limited number of tasks. They use rule-based programming to match user queries with potential answers, typically for basic FAQs. Where basic chatbots show their limitations is if they receive a request that has not been previously defined; they will be unable to assist, and spit back a “Sorry, I don’t understand.” response.
In order to meet the requirements of larger organizations like banks, insurance companies and telcos, chatbots need artificial intelligence to enhance their ability to understand human language and perform more complex tasks and transactions. In relation to chatbots, this branch of artificial intelligence is called conversational AI.
We build virtual agents that are more powerful and capable than ordinary chatbots. Here’s how:
We can build a solution faster than anyone else. After just a few days, the virtual agent is operational and ready for testing. We include a report on expected resolution rate and potential cost savings.
Our intuitive no-code conversational AI platform empowers frontline teams to automate customer service without tech support. Because with boost.ai, you don’t need developers to automate.
If a virtual agent can’t understand, it won’t be able to help. It’s why NLU is so crucial for successful automation. Our market-leading NLU gives our virtual agents consistent resolution rates of over 90% - in any language.
In order to help someone, you have to first understand what they need help with.
Machine learning can be useful in gaining a basic grasp on underlying customer intent, but it alone isn’t sufficient to gain a full understanding of what a user is requesting.
Using sophisticated deep learning and natural language understanding (NLU), it can elevate a customer’s experience into something truly transformational. Your customers no longer have to feel the frustration of primitive chatbot solutions that often fall short due to narrow scope and limitations.
Learn why Natural Language Understanding matters for virtual agents
(5 min read)
By up-skilling parts of their trusted customer service teams into AI Trainers, companies are keeping conversational AI on-brand.
AI Trainers use the technology to automate large-scale interactions between brands and consumers, relieving their teams of mundane and repetitive work, while losing none of the customer service level they pride themselves on.
Learn more about how they design interactions
(4 min read)