About us

Launched on July 8, 2016, this project began with an ambitious goal: to create a chatbot capable of emulating human conversation.

Our journey started simple—using basic text files for direct sentence-matching. However, reading and modifying flat files quickly proved inefficient, leading us to transition to a dynamic database system that dramatically streamlined our data management.

Recognizing that simple sentence matching was too rigid, we evolved our approach by integrating a dictionary database to analyze parts of speech (nouns, verbs, adjectives). This allowed our engine to extract intent and store key terms rather than full static lines. From there, we built a syntax engine that reformulates user inputs into questions, suggestions, or statements by applying core grammar rules and adjusting perspectives (like mapping "I" to "you").

To make conversations flow naturally, the system tracks keywords across sessions—summarizing context every few exchanges to pull relevant memories from the database. Today, we are pushing the boundaries further by teaching the system to self-correct, bringing us one step closer to true AI.