Comparing RAG approaches for semi-structured data
A paper published on June 25, 2026 presents a framework for comparing four RAG approaches across nine standardized scenarios.
Source: Framework para comparar abordagens de RAG em dados semiestruturados (arxiv.org). Text prepared with AI from this source.
What happened and what to do
Published on June 25, 2026, the paper presents a framework for evaluating regular, Graph, Modular, and Agentic RAG on semi-structured knowledge bases. It implements nine standardized scenarios and compares the approaches in settings with data and domain constraints.
A company can apply this kind of evaluation to its own data: define representative scenarios, test approaches with the same questions and constraints, and monitor quality, latency, and cost. Based on the results, it can select an architecture and implement the required retrieval, APIs, and dashboards without defaulting to agents.
How the consultancy can help
Wendelmaques can diagnose the opportunity and data constraints, define an evaluation plan suited to the domain, and deliver a scoped implementation, including a retrieval pipeline, APIs, and monitoring. Ongoing operation can also be included in the scope.
Next step
Send a short description of your knowledge base, the questions it needs to answer, and your constraints to receive a scoped proposal.
Let's assess your project
I reply with scope and a proposal.