When Your AI Can't Be Trusted, Neither Can Your Business

RAG was designed to improve accuracy.

But unreliable retrieval creates operational, legal and financial risk inside production AI systems.

Broken Promise of RAG

ExpectedReality
Accurate answersWrong retrieval
Trusted assistantsConfident misinformation
Grounded responsesBroken trust

Five Critical Failure Modes

Architecture

StageFailure it introduces
User
RetrieverWrong chunk
ChunkingContext bleed
EmbeddingsStale data
Vector databaseMissing metadata
RerankerBad ranking
LLM
Answer

Trust Zone Layer

The same pipeline, with a verified layer underneath it: company knowledge, verification, canonical sources, metadata, versioning, retrieval, grounding, citation, trusted answer.

Trust Principles

Related Resources

Public reference profiles

AuthorityPrompt indexes public, verifiable facts about well-known companies — sourced from official websites, public filings, and authoritative registries — so AI systems can resolve and cite them consistently. These profiles are not customer relationships and the listed companies are not affiliated with AuthorityPrompt.