Breaking the EDI Bottleneck: Modern Mapping Through Generative AI (Published)
Electronic Data Interchange (EDI) is an established technology in the integration of an enterprise but the conventional mapping procedures are limited by the high levels of manual work, limited reuse and long cycles of partner onboarding. This paper describes a generative artificial intelligence (GenAI)-based system to automate EDI mapping based on schema-sensitive prompt engineering, metadata-based design, and validation-based generation of transformations. Unlike other methods which are rule-based and thus static, the intended solution is dynamically generated to produce transformation logic and adapt to the variations in data of partners.A case study of production that entailed around 200,000 monthly EDI transactions has shown that up to 70% of the onboarding period and 60 percent of the mapping work was reduced. These findings imply that GenAI has the potential to convert EDI workflows to manual setups to an automated system of intelligent, scalable, and adaptive integration.
Keywords: ANSI X12, B2B Integration, Cloud integration, Data Mapping Automation, EDI, enterprise AI, generative AI
Semantic Data Contracts: A New Integration Paradigm for Enterprise AI and Database Systems (Published)
Semantic data contracts represent a paradigm shift in enterprise AI-database integration. While traditional approaches focus primarily on structural compatibility, semantic contracts establish explicit agreements about data meaning, quality, freshness, and permissible usage patterns. These contracts create a bidirectional understanding layer that enables sophisticated decisions about query routing, data materialization, and privacy preservation that current approaches cannot adequately support. The implementation requires a multi-layered strategy encompassing semantic modeling, contract specification, mediation layer development, monitoring systems, and governance frameworks. The value of these contracts is evident across healthcare, financial services, supply chain management, and customer experience domains, where data interpretation directly impacts decision quality.
Keywords: bidirectional understanding, data contracts, enterprise AI, ontology modeling, semantic integration