Semantic Web / GenAI enabled EAI (Enterprise Application Integration) Framework
This post covers the inception phase documentation links related to a novel approach of doing EAI through the use of Functional / Reactive Programming leveraging GenAI and Semantic Web (graphs) and also the implementation of a novel approach of doing embeddings, not only for similarity calculation but also for relationships inference, query and traversal in an algebraic fashion.
Introduction
In today's competitive landscape, organizations are often hampered by a portfolio of disconnected legacy and modern applications. This creates information silos, manual process inefficiencies, and significant barriers to innovation. This Unified Application Integration Framework project is a strategic initiative designed to address these challenges head-on.
The project's core goal is to "integrate diverse existing / legacy applications or API services" by creating an intelligent middleware layer. This framework will automatically analyze data from various systems, understand the underlying business processes, and expose the combined functionality / use cases through a single, modern, and unified interface keeping in sync this interactions with the underlying integrated applications backends.
Approach
Implement Semantics (graphs) / AI enabled Business Integration / Enterprise Application Integration (EAI) platform with a reactive microservices backend / functional programming leveraging GenAI. Currently trying to specify the frameworks, techniques and patterns used for the implementation.
Particularly novel is a custom way to encode embeddings, enabling GenAI / MCP custom interactions (not just similarity but also relationships inference). There left to be built a proof of concept about this proposal and the overall architecture, choosing the right components and tools layout before moving into the implementation phase. This includes evaluating which GenAI models and tools could be used somehow leveraging this approach.
Goal
The idea is to build a layered semantic (RDF4J) set of models with their own levels of abstraction backing a set of microservices (Spring) from data ingestion from integrated business / legacy applications, their datasources, files and APIs to an Activation layer which exposes a unified interface to the integrated applications use cases keeping in sync integrated applications backend with this layer's interactions.
Implementation
RDF / FCA (Formal Concept Analysis) for inference in an Aggregation layer, an FCA-based embeddings model for an Alignment layer and DDD (Domain Driven Development) / DOM (Dynamic Object Model) / DCI (Data, Context and Interaction) and Actor / Role Pattern for the mentioned Activation layer.
Reference documents
https://github.com/sebxama/sebxama/raw/refs/heads/main/ApplicationService.pdf
https://github.com/sebxama/sebxama/raw/refs/heads/main/RoadmapDetail1.4.pdf
Implementation Roadmap (Work In Progress, needs cleanup). Start reading RoadmapDetail3.1.pdf and RoadmapDetail3.6 (Algebraic Embeddings) to see if it is worth for you to continue reading:
https://github.com/sebxama/sebxama/raw/refs/heads/main/RoadmapDetail3.0.pdf
https://github.com/sebxama/sebxama/raw/refs/heads/main/RoadmapDetail3.1.pdf
https://github.com/sebxama/sebxama/raw/refs/heads/main/RoadmapDetail3.2.pdf
https://github.com/sebxama/sebxama/raw/refs/heads/main/RoadmapDetail3.3.pdf
https://github.com/sebxama/sebxama/raw/refs/heads/main/RoadmapDetail3.4.pdf
https://github.com/sebxama/sebxama/raw/refs/heads/main/RoadmapDetail3.5.pdf
https://github.com/sebxama/sebxama/raw/refs/heads/main/RoadmapDetail3.6.pdf
This documents covers just the starting of the specification and design phases. Advice is welcome in this initial phase about tools and implementation choices.
Regards,
Sebastián Samaruga.
https://github.com/sebxama/sebxama
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