Compare Dexter vs. Moonoia docBrain

Generating customs declarations has become remarkably straightforward. Just upload your invoices, packing lists, delivery notes, and any other relevant customs paperwork to Dexter, who will handle the rest while you concentrate on higher-value tasks. By leveraging his extensive customs knowledge, Dexter addresses both the lack of skilled labor and the need for manual data entry in the customs declaration process. The integration of Dexter requires minimal effort on your part and can save you anywhere from 3 to 90 minutes per customs case starting from the very first day. He seamlessly manages the entire workflow, turning raw customs documents into submission-ready declarations for authorities with exceptional accuracy. You can process an array of documents, including today's invoices and tomorrow's bills, regardless of their size or language. Dexter is equipped to read and comprehend a diverse selection of customs documents, and you can also develop your own extraction models if desired. Furthermore, Dexter intelligently interprets the extracted data, ensuring that it aligns perfectly with your master data for optimal efficiency. Overall, Dexter transforms the customs declaration experience into a streamlined and efficient process.

The docBrain platform unites various fields including machine learning, data science, solution engineering, and DevOps, focusing on enhancing productivity in document-centric tasks. By leveraging deep learning technology, you can build AI models from scratch, tailoring solutions to meet your specific document-related issues effectively. Additionally, docBrain offers pre-trained models, enabling users to benefit from extensive prior learning and guaranteeing a solid return on investment before engaging in any training activities. Whether you opt to train the AI yourself or utilize readily available models, the solutions you implement through docBrain will seamlessly connect with your existing business infrastructure. Developed internally, docBrain was designed to tackle Moonoia’s unique document processing hurdles, which were primarily caused by manual data validation that was both error-prone and expensive, ultimately hindering automation efforts. Furthermore, existing OCR technologies in the market failed to deliver the level of accuracy needed for efficient straight-through processing, particularly when dealing with handwritten, unstructured, or low-quality documents, thus underscoring the necessity of such a platform. This innovative approach not only enhances operational efficiency but also paves the way for more reliable document management solutions in the future.