  In this paper, we present a hybrid model that combines a neural
conversational model and a rule-based graph dialogue system that assists users
in scheduling reminders through a chat conversation. The graph based system has
high precision and provides a grammatically accurate response but has a low
recall. The neural conversation model can cater to a variety of requests, as it
generates the responses word by word as opposed to using canned responses. The
hybrid system shows significant improvements over the existing baseline system
of rule based approach and caters to complex queries with a domain-restricted
neural model. Restricting the conversation topic and combination of graph based
retrieval system with a neural generative model makes the final system robust
enough for a real world application.
