Our XAI models combine deep learning’s pattern recognition capabilities with symbolic AI’s logical reasoning. These models incorporate explicit rules and domain knowledge alongside machine learning, providing clear explanations for their decisions. They deliver both performance and transparency, making them an excellent choice for healthcare, finance, and other regulated industries. With built-in reasoning capabilities and clear decision paths, these models ensure reliable, accountable AI-driven solutions.

Traditional deep learning models, widely used across industries, rely on purely data-driven neural networks trained on extensive datasets to excel at pattern recognition tasks. While they often achieve impressive accuracy and can handle complex inputs like images, speech, and text with ease, they typically lack the transparent reasoning features crucial in regulated or safety-critical domains. They are frequently considered “black boxes,” making it difficult to derive a clear rationale behind their predictions.