Every business and individual is unique. They have their own unique spoken languages and workflows for their daily operations. When you visit a doctor, you speak in specific ways to complete a set of workflows. When you visit an eCommerce site, you follow the workflows of that site to complete your shopping.
In each of these businesses, employees and customers use unique combinations of language and workflows as they go through their transactions. Over time, employees of an enterprise get smarter with cumulative knowledge of how things are done, and they transfer this accumulated knowledge to newcomers.
Now, imagine a future where AI has advanced to comprehend what we say, foresee what we need to do next, and then provide the needed assistance to expeditiously complete these tasks and produce the desired outcomes. In order to accomplish this, we need Spoken Language Understanding (SLU).
Here of some of the key abilities of SLU:
- Support Unique Terminologies: In any business context, we use terminologies that are only understood by colleagues and other people in this specific environment. For example at a doctor’s office, when a patient engages with the front-desk, where the doctor’s assistant enquires about various facets and symptoms of the patient’s health. The assistant uses terminologies, both words and abbreviations, that are understood by the patient as well as by doctors and other medical staff. However, saying these same terms outside of the office will only confuse people.
- Assist Unique Workflows: Each business defines its own set of workflows for its daily operations and the answers to specific business-related questions define subsequent workflows. However, these answers can differ, with each variation leading to a different step in succeeding workflows. The entire workflow is unique to a user, based on context, answers, and needs. For example, in a doctor’s office, if a patient has a cold, the subsequent set of questions (in the workflow) will vary, based on expressed symptoms and their severity.
- Provide Collective Intelligence: We all possess knowledge. When we share it with others, we contribute to the collective intelligence of a group. That knowledge and intelligence keep increasing over time, with every interaction. For example, in a doctor’s office, a nurse learns a medical procedure by asking questions such as “how do I do this”, “what do I use”, and “when does it need to be done”. The knowledge accumulated by the nurse, when shared with colleagues, who later practice it, increases the collective intelligence of the group.
In summary, an SLU Intelligence Foundation for each business should a) support unique terminology, b) assist unique workflows, and c) promote collective intelligence. Similar to the healthcare use case examples provided above, SLU can be applied to a variety of industries such as eCommerce, banking, health&fitness, and many more.
Alan AI is a SLU-based Conversational Voice AI Platform that understands and learns nuances of spoken language in a context, to deliver superior responses to questions, commands, and requests. It is also a discovery tool that can help and guide users with human-like conversational voice through any workflow process.
Using Alan’s self-service platform, you can build a SLU Intelligence Foundation for any business and application. With continuous usage and data coming from the application and its previous user interactions, it will become the intelligence foundation for your enterprise.