 FinTech Summit Spring Session: soetek Cooperates with Tricentis to Drive ERP Toward AI Governance As digital transformation enters uncharted deep waters, artificial intelligence (AI) is shifting from experimental phases to core corporate strategies, and Enterprise Resource Planning (ERP) systems are progressively upgrading into corporate decision-making centers. soetek has joined forces with Tricentis to deploy objective-driven frameworks and Agentic AI technology. This collaboration assists enterprises in boosting productivity and strengthening competitiveness while maintaining high quality and regulatory compliance, thereby unlocking the value of data assets in the AI era. soetek’s 3-Stage Framework Eases Corporate AI Anxiety Addressing the widespread anxiety surrounding corporate AI deployment, Po-Ting Lin, General Manager of the Intelligent Enterprise Solutions Business Group at soetek, noted that AI implementation should follow a three-stage framework: "Objective-Driven, Process Analysis, and Continuous Optimization." Companies should prioritize high-consumption and bottleneck processes, incrementally optimize them using AI modules, and continuously evaluate the return on investment (ROI).
Taking credit risk assessment in the banking sector as an example, traditional processes typically take anywhere from 3 to 14 days, with data collection and financial analysis occupying most of that time. By utilizing Robotic Process Automation (RPA) and Intelligent Document Processing (IDP) to automatically extract data, enterprises can shave off roughly 70% of operational time. If generative AI is further integrated to automatically generate credit evaluation reports, productivity can jump threefold while error rates plummet by 90%, successfully transforming data centers into highly efficient, intelligent corporate brains. Tricentis & soetek Build Comprehensive Automated Validation Platform However, as AI accelerates code development and system changes become more frequent, enterprises face heightened challenges regarding system quality and stability. Remmy, Director of Strategic Alliances and Channels for North Asia at Tricentis, pointed out that by 2025, approximately 40% of global code was already being generated by AI. If this code is deployed directly without comprehensive validation, it significantly elevates operational risks. With SaaS applications updating at a breakneck pace, traditional manual testing can no longer keep up, making automated testing capabilities a decisive competitive edge for modern enterprises.
He emphasized that AI cannot solve problems relying solely on models; it must be coupled with actual business scenarios and full-application coverage to truly unlock the strategic value of data. Within the Tricentis AI Quality Engineering Platform, SeaLights oversees quality analysis and risk identification, Tosca focuses on continuous automated validation, Data Integrity reinforces data validation and source matching, NeoLoad targets system performance and load testing, and qTest supports test lifecycle and agile team management. Furthermore, the platform integrates Agentic AI and the Model Context Protocol (MCP), allowing it to interface with an enterprise's existing AI architecture, proactively identify latent risks, and help users swiftly achieve precise results.
As we march into the era of AI governance, soetek combines the application depth of SAP with the comprehensive testing breadth of Tricentis. This synergy helps enterprises construct a robust, highly efficient digital foundation, drastically shortening the time-to-market for innovations while minimizing transformation risks—ensuring that AI truly becomes the growth engine for corporate productivity. |
