Humanizing RAG

At the frontier of AI systems, Retrieval-Augmented Generation (RAG) has emerged as a cornerstone in the orchestration of grounded, high-fidelity outputs. Yet, despite its architectural elegance, RAG remains fundamentally nontrivial for business stakeholders, product teams, and non-technical users to orchestrate, validate, and trust.

We are building a cognitive abstraction layer, a Customer Experience (CX) Layer for RAG , that transforms unstructured LLM output pipelines into structured, explainable, and controllable user experiences.

This is not just a UI wrapper. It is a semantic interface paradigm for the post-foundation model era, where retrieval, generation, and human judgment converge.

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