In a recent Memgraph Community Call, Dr. Yoan Sallami, CEO of SynaLinks, detailed the potential of neuro-symbolic AI frameworks in enhancing the flexibility and adaptability of LLM-powered systems through the integration of knowledge graphs. SynaLinks, inspired by Keras, is designed to facilitate dynamic, self-organizing agents by leveraging structured workflows, flexible knowledge graphs, and robust business optimization. The framework employs directed acyclic graphs (DAGs) for its pipelines, ensuring consistency and ease of use akin to Keras, and uses Pydantic models for data serialization. Knowledge graphs within SynaLinks are adaptable, supporting diverse business needs with schema flexibility, and can handle complex entity extraction through multi-stage processes that optimize control and accuracy. The talk also highlighted a practical demonstration of SynaLinks' integration with Memgraph, showcasing its real-time graph growth and deduplication capabilities using HNSW indexing. Dr. Sallami emphasized the importance of expert-guided schema design to ensure effective knowledge graph applications, which are currently being applied in fields such as security, biology, finance, and healthcare for their ability to provide clear insights from relational data.