The product is an enterprise chatbot platform which can serve different use cases for external customers and employees. It is capable of assisting with complex tasks such as answering questions, providing information, and completing processes. It uses deep learning based large language models and large scale knowledge graphs for better accuracy and timeliness. The chatbot's design is intuitive and powerful, allowing for easy design without coding. Additionally, data-centric solutions are provided to facilitate onboarding of use cases and improve chatbot performance.

One of the key benefits of an enterprise-grade chatbot is its ability to assist with complex tasks. That enable them to understand and respond to complex user queries. This means that they can provide information, answer questions, and even complete processes, such as booking an appointment, making a purchase, or resolving a support ticket.

The accuracy of a chatbot is critical to its success. The chatbot uses deep learning-based algorithms that enable it to achieve high accuracy and cover a wide range of tasks. Specifically large language model (LLM) and large scale knowledge graph technologies are used to allow the chatbot to accurately understand customer's intent and continuously learn from its interactions with users.

Creating a chatbot can be a complex process, our product comes with intuitive and powerful design tools that allow chatbot designers to create and customize chatbots without any coding. These tools include drag-and-drop interfaces, pre-built templates, and a range of design elements that can be easily configured to match the brand and voice of the organization. Chatbot designers can also use these tools to add custom workflows and integrations with other systems, such as CRM or support tools.

The chatbot is designed to be data-centric, which means that it uses existing data to quickly build a chatbot, including existing customer-agent conversations, enterprise documents, and product manuals, etc. The chatbot can capture and analyze user interactions, identify patterns, and make recommendations for improvements. This data-centric approach makes it easy to onboard new use cases and optimize the chatbot's performance for specific business needs. Chatbot designers can easily refine the chatbot's conversational abilities, improve its accuracy, and ensure that it provides a seamless user experience.