Graph databases offer unparalleled flexibility for managing interconnected data, yet the lack of strict schema enforcement often leads to runtime uncertainties and complex query development. This paper introduces Graphify, an end-to-end framework that enables developers to visually model graph data schemas and automatically synthesize a fully functional, type-safe backend. This paper proposes a formal mapping of GraphQL artifacts to the Gremlin traversal machine, supporting complete CRUD operations and arbitrarily nested queries. The system generates a transpiler capable of converting complex GraphQL requests into a single, optimized Gremlin query, including advanced features such as nested logical predicates, multi-key sorting, and pagination. At the core of the framework is a recursive state machine algorithm that processes GraphQL Abstract Syntax Trees (ASTs) with linear time complexity $O(S)$ relative to the number of selected fields. This paper demonstrates the practical efficiency and theoretical robustness of the approach through formal complexity analysis and empirical evaluation using the MovieLens 100k dataset. The result is a system that enables the generation of graph interfaces in minutes, bridging the gap between flexible graph storage and type-safe API consumption.

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