This reflection-integrated palindrome detection model combines neural network text processing with a custom character reflection score to achieve perfect palindrome detection. The model uses a dual-input architecture that processes both text encoding and reflection scores, providing comprehensive insights into symmetry patterns. The reflection score measures character-by-character symmetry through vector analysis, while the model provides real-time visualizations including character similarity heatmaps, symmetry analysis, and detailed vector breakdowns. This approach demonstrates how neural networks can be enhanced with domain-specific features to achieve exceptional performance. Supports inputs of 1-50 characters with automatic model loading and unloading.