The DialogFlow engine can be effectively used for building conversational applications for any industry or business where there is a requirement for a human agent to answer client queries or perform a set of preconfigured actions. With voice interaction and a strong NLP engine, the conversations sound natural, and if they are configured extensively, it is difficult for the caller to differentiate between a human agent and a DialogFlow agent.

DialogFlow agents offer serverless access to ML models that are internally trained during the development and configuration process. All the nonfunctional aspects and features supported by GCP are inherently available to the DialogFlow agent. Some of the significant advantages are scalability and availability. If the service encounters a large volume of traffic and API requests, the cluster is autoscaled to fulfill the increase in demand for computational resources. The platform also ensures 99.9% availability because of the use of the underlying GCP infrastructure.

This is helpful for seamlessly providing 24/7 customer support for services. For example, in the case of an airline agent, the customers can inquire about flight schedules, book flights, or perform web check-ins with the conversational interface provided by DialogFlow. The agent can be available 24/7 for these services, which improves service levels and reduces the cost of operation significantly. The agent can be integrated with the client's CRM system in order to handle certain requests that the agent is not trained to handle. As the service is utilized, the logs are analyzed, and a feedback loop is established, the quality of the conversational agents improves over a period of time.