There is really no AI problem afflicting the organization because the problem is data and trust that makes it more visible. Organizations have their data spread across the ledger, orders, customers, business rules, and workflows.
The challenge lies in ensuring that AI has access to the needed context with both the necessary permissions and restrictions.
Every organization has its own data, risk characteristics, and ERP configuration, which is why we are customizing the solutions, not selling them in the off-the-shelf version.
Integrate SAP Business AI, Joule, AI agents, and SAP BTP into business processes using the appropriate data, processes, permissions, and controls for business purposes.
Explore →The success of Enterprise AI relies on what comes below it. This is the foundation we put together before and after launch.
We organize and clean the data coming from ERP and business processes to make sure that the information used for model training is trusted by the company.
We provide access to our models according to the tasks they perform. Our models may be audited, and each decision made by them can be explained.
Our models are created using systems compatible with SAP BTP, AWS, or Azure platforms, and all existing data.
We support dialog robots and autonomous agents capable of making calls to ERP and CRM application programming interfaces.
Detecting drift and retraining models guarantees accuracy of forecasting and early detection of abnormal conditions.
Dashboards reflect what AI has detected, processed, or reported; they are created for CFOs and COOs instead of data departments.
We are working the same way as for SAP and NetSuite projects.
Evaluate data, risks, and maturity of processes. Evaluate possible applications by ROI.
Implement a pilot project, going live in 8-12 weeks.
Apply the same AI functionality in different departments and processes.
We manage and control the models as the business develops.
AI utilizes the machinery and sensors within significant activities to help foresee malfunctions before any downtime and identify quality problems at an earlier stage.
Explore More ↗Custom AI models can check the batch records against the regulations, saving the processing time behind every batch released here.
Explore More ↗AI is able to predict the demand for each SKU and personalize products for sale along the way; therefore, the business will have fewer products while its sales grow.
Explore More ↗AI works out the route and loading plans from the very beginning in line with current live conditions thereby saving on fuel costs and avoiding any missed opportunities to deliver orders.
Explore More ↗AI has been trained using telemetry data from machines to show early warning signs in remote and highly dangerous modes of operation.
Explore More ↗Computer vision training has allowed the AI to catch all defective products on the production line much faster and more reliably than manual quality control.
Explore More ↗From AI solutions and cybersecurity to SAP, custom models, and implementation.
AI automation, AI cybersecurity, custom-made AI model development, SAP AI on BTP and Joule, ERP automation, and AI workflow automation all of these solutions are embedded within the client's ERP, cloud, or security stack, instead of being available separately.
It takes into account typical network, user, and system behavior, and distinguishes abnormal situations, for example, unusual access, transfer, or sign-in behavior.
It is trained on the data and rules of the organization. The output will correspond to the organization's accounting chart, catalog, or clinical protocol. We are using SAP BTP, AWS, or Azure to obtain the information we need.
SAP AI includes machine learning and generative AI, which are in S/4HANA, BTP, and Joule. We implement these solutions first before applying a custom model where SAP's native AI can't perform a certain process.
It usually takes about 8 to 12 weeks to implement a single-process pilot project, for instance, an AI-powered cash application or anomaly-based threat detection.
A 45-minute review of your data, systems, and the AI use cases most likely to pay back first.