LinePulse is an AI-powered Supply-Chain Intelligence platform aimed at manufacturing companies and the industry. Many manufacturers only recognize problems with suppliers when they already have an impact on production and deliveries. Relevant information is often scattered across ERP systems, spreadsheets, emails, supplier notifications, and informal communication. LinePulse consolidates this data and uses Machine Learning to identify risks such as delivery delays, capacity constraints, and potential disruptions early on. Subsequently, their possible impact on production and supply capability is analyzed and concrete measures for risk mitigation are proposed. The goal is to lead companies from reactive problem-solving to proactive, data-driven supply chain management, without the need to replace existing systems.

The project develops compact, programmable controllers and intelligent automation solutions that combine classic control functions with modern embedded systems, connectivity, Industrial IoT (IIoT) and AI. The devices are based on modern microcontrollers and SoC modules and can run AI applications such as anomaly detection, predictive maintenance and intelligent process optimization directly on the device. By using industrial networks such as Ethernet and Modbus, the systems remain compact, cost-effective and easily expandable. First prototypes are a programmable smart relay and a compact PLC platform. The goal is intelligent control solutions for industrial automation, machine tools, building automation, robotics and special machines. In addition, customer-specific control systems are to be developed. The first commercial product and the target market are defined based on customer requirements and financing options.

We are building a payment orchestration layer for Tanzanian merchants, connecting them to banks and existing payment rails through a single API. Removing the burden of integrating separately with every bank and mobile wallet, reducing both cost and complexity.