From 4d37920007e75289fe80a40651250cb6aa27cc10 Mon Sep 17 00:00:00 2001
From: Mohd Kaif <98801504+KaifAhmad1@users.noreply.github.com>
Date: Sun, 16 Aug 2026 17:51:23 +0530
Subject: [PATCH] docs: surface explainability scope note near the top of the
 README (#1034)

Moves a concise version of the system-level vs. foundation-model
explainability clarification up next to the opening pitch, so it's
visible before readers scroll to the high-stakes-domains section.
---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index 58afaf3f..8b89fd5f 100644
--- a/README.md
+++ b/README.md
@@ -52,6 +52,8 @@ Most AI agents act without a trail. They store embeddings, not meaning: context
 
 Semantica sits underneath your LLM, vector store, and agent framework as a deterministic infrastructure layer: no LLM required for graph construction, reasoning, or provenance.
 
+> ⚠️ **System-level explainability, not foundation-model explainability.** Semantica does not expose or reconstruct what happens *inside* the LLM — its internal reasoning or chain-of-thought stays opaque, as it does for any external system. Semantica explains what's *outside* the model: the context and data fed in, the decision produced, its provenance, relevant relationships, applied policies, and the full execution trail.
+
 **Who it's for:**
 
 - **AI/ML platform teams** shipping agents that make consequential decisions and need structured, queryable context built from fragmented raw data, not just a vector index