We combine state-of-the-art AI technologies with our proven process and SAP expertise. Our goal is ambitious:
Invoices are posted automatically in the background in SAP – without manual intervention. The future of accounting starts now.
Upgrading conventional capture technologies. Our software uses large language models (LLMs) to capture document content more intelligently, with higher recognition, fewer errors, and less manual rework— enabling true automation.
Our Prediction Server simplifies invoice processing in SAP. The AI suggests account assignments, identifies the right clerk, company code, and supplier. This speeds up approvals, reduces errors, and improves overall efficiency.
Many companies today are grappling with a shortage of skilled accounting staff. Our AI handles repetitive tasks, freeing up employees to focus on high-value activities. With xSuite AI solutions, the skills shortage becomes a minor concern.
The biggest source of errors in automated invoice processing? Document reading. Traditional capture systems are error-prone and demand time-consuming corrections. AI significantly refines their results.
With xSuite's use of large language models, the effort required for capture projects is reduced by up to 80%, while recognition rates can increase to 95%.
But there’s more. Our Prediction Server offers intelligent support for invoice processing, including:
Automatic suggestions for G/L accounts, cost centers, internal orders, etc.
Dynamic fraud protection through predictive analytics.
With dynamic fraud protection, the AI analyzes historical transactions to detect suspicious patterns before payments are released. Unusual amounts? Unknown suppliers? Recurring questionable invoices? Our AI raises the alarm before any damage occurs.
AI enables faster, more accurate, and more secure invoice processing. With xSuite, take the next step toward full automation and harness the power of artificial intelligence today.
Various AI technologies are used in the xSuite solutions. The suggestion functions in the workflow (Prediction Server) are based on deep learning. Document reading is a mix: simple steps, such as self-learning supplier training, are based on machine learning. An R-CNN model (Region Based Convolutional Neural Network) is used for image recognition. It is also possible to use a large language model for document capture.
Artificial intelligence is the generic term for applications that demonstrate human-like intelligence and can solve problems. One sub-area of this is machine learning, in which algorithms learn from data to recognize patterns and make predictions without being explicitly programmed. Deep learning, on the other hand, is a specialized form of machine learning that is based on artificial neural networks with many layers and is particularly efficient with large amounts of data and complex tasks. While artificial intelligence encompasses many different methods, machine learning is a specific approach, and deep learning is the most advanced form of it.
With the use of LLM models, significant improvements in document reading can be achieved in two areas. A central point is the recognition rates. An improvement from 85% to 95% recognition rate at field level is realistic. In addition, the effort required for a capture project is reduced by up to 80%.
Absolutely. The AI provides suggestions. When confidence is high, entries may be auto-filled – but a verification step always remains in place. AI is designed to assist, not replace, human oversight.
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