README.md
KESPA-NOTE-015 — Trusted Knowledge Indexing Boundary and Private-Data Exclusion
Date: 2026-09-14 Status: Verified — live production indexing confirmed Project: KESPA AI / NexLabs Studios
Purpose
After the clean 423-claim production cutover, KESPA needed a controlled way for newly promoted trusted knowledge to enter live semantic retrieval.
The indexing path could not simply accept arbitrary candidate text.
It also had to preserve the privacy boundary between:
- public promoted knowledge; and
- internal/private training material.
Indexing contract
The production architecture established:
MySQL trusted_knowledge = authoritative
Chroma forge_cards = rebuildable semantic index
The live Brain added an authenticated:
POST /knowledge/index
for promoted knowledge ingestion.
The path allows public promoted trusted knowledge to enter forge_cards.
It explicitly blocks internal/private plaintext from the public promoted-knowledge Chroma indexing path.
Why that separation matters
A vector database is optimized for retrieval, not for being the canonical trust ledger.
KESPA therefore keeps lifecycle state, provenance, verification, approval, and authoritative knowledge records outside Chroma.
Chroma can then be rebuilt from trusted records if needed.
The index answers:
What trusted information should be retrieved for this query?
It does not decide:
What information deserves to be trusted?
First live validation
The clean production index started at:
423 cards
The first promoted trusted record was indexed:
trusted_knowledge #1
Recorded indexed card:
trusted-knowledge-b645128e-7020-4639-9e3e-7a21aaf36fc8
Production index version:
dev-013-trusted-knowledge-index
Observed result:
- before: 423
- after: 424
- index status: indexed
- intended-query rank: #1
- website card counter reflected the live index
Result:
PASS
Privacy boundary
The same architecture keeps internal/private Manual Train material outside the public external-evidence/index path.
That means the system does not solve knowledge growth by flattening every data class into one vector store.
Public knowledge and private/internal material retain different lifecycle rules.
Research significance
This is a small but important control for continuous learning.
Without an explicit indexing boundary, a system can have excellent verification logic and still contaminate live retrieval by allowing unpromoted or private material to bypass the trust lifecycle.
KESPA instead requires:
candidate -> verification -> approval -> promotion -> indexing
for public trusted knowledge.
Limitation
This note proves the production indexing path and its data-class boundary.
It does not claim that one #1 retrieval result is a broad quality benchmark; retrieval effectiveness is evaluated in separate benchmark records.