Executive Summary
No retrieval architecture, however well engineered, can produce a good answer from a bad document. Vertiva's platform is deliberately architected around that reality: ingestion, classification, and chunking are treated as first-class engineering problems with their own governance.
Retrieval Quality Has a Ceiling, and Data Sets It
Independent analysis of production RAG deployments finds that a large majority of retrieval failures — commonly cited around 80% — originate in the ingestion and chunking layer, not in the language model itself. Controlled studies changing only the chunking strategy have shown accuracy swings of twenty to seventy-plus percentage points.
Figures reflect published 2026 industry analyses of production RAG deployments; cited as general context, not as claims about any specific customer's results.
How Vertiva Engineers Data Quality by Construction
One path in, with provenance attached at the door: every source normalizes into the same ingestion path and produces a sidecar record capturing source URI, trust level, and checksum.
A staged (bronze/silver/gold) pipeline: raw content is kept immutable; only validated, serving-ready artifacts reach the vector store, lexical index, and knowledge graph.
A quarantine zone: documents that fail classification or a malware/PII-egress flag are routed to quarantine rather than the retrieval index.
Classification is validated, not just declared at the point of ingestion.
Federated Retrieval Hedges Against the Limits of Any One Method
Vertiva fans every query out across semantic, lexical, and knowledge-graph retrieval simultaneously. A chunking or embedding weakness in one modality doesn't automatically become a wrong answer — a different retrieval path frequently still finds the right context.
A Shared Responsibility, by Design
Vertiva's side: governed ingestion, classification validation, federated retrieval, embedding-model governance, and continuous evaluation.
The customer's side: clean, current, well-classified, and de-duplicated source documents.
The Bottom Line
The data-onboarding workstream in every customer rollout includes an explicit source-data quality pass alongside the access-control validation it already performs. Customers who invest in ingestion hygiene at onboarding see compounding retrieval-quality benefits across the entire platform.