In this study, Convolutional Neural Network (CNN) with Recurrent Neural Network (RNN) is used to enhance character recognition of Brahmi script. Natural Language Processing (NLP) tools are used to improve the understanding of the characters which are faded due to any reason. The model was evaluated using CNN, Long Short-Term Memory (LSTM) and NLP techniques. Based on the results, the proposed approach is capable of recognizing Brahmi characters with high accuracy, especially in printed text. Handwritten text, particularly those with varying handwriting styles, still pose a challenge but can be effectively managed with the integration of sequential models like LSTM. NLP-based corrections enhance the overall accuracy by providing context-aware recognition, making the model more robust in interpreting noisy or ambiguous text. Overall, the proposed model extends the accuracy of character recognition of Brahmi script.