Mapping out how the chatbot interacts with users, including common questions and responses, requiring careful consideration of legal terminology.

Building the backend logic to handle user inputs, responses, and maintain context during conversations.

Integrating NLP tools to facilitate understanding of user queries, needing time for training and testing the model.

Linking the chatbot with existing systems for appointment scheduling or accessing case details, which will vary based on API documentation.

Creating an interface through which users can interact with the chatbot, involving wireframe design and visual elements.

Conducting user testing to ensure the chatbot functions correctly and accurately responds to a variety of inputs before going live.