Enterprise AI & Agentic AI
What is enterprise RAG and when do you need it?
Enterprise RAG grounds model answers in your own governed content: documents are chunked, embedded and retrieved at query time, then cited in the answer, with the user's permissions enforced on retrieval. You need it whenever answers must reflect current, access-controlled company knowledge — policies, product data, contracts — which is most enterprise use cases.
Last reviewed 2026-08-31 · pronix.ai
Key takeaways
- Permissions at retrieval timeAccess control is applied when documents are retrieved, not filtered after generation — otherwise the model can leak content the user cannot open.
- Citations make answers auditableEvery generated answer links back to the source passage, which is what makes RAG acceptable to risk and compliance teams.
- Content quality dominates accuracyMost RAG failures trace to stale, duplicated or unstructured source content rather than to the model or the vector store.
What the numbers show
First-party figures from Pronix research. Each links to the report or playbook that publishes it.
- 31%
- Retrieval, integration and evaluation infrastructure is now the single largest line in the enterprise AI budget at roughly 31% of spend.Source: State of Agentic AI in the Enterprise 2026 →
- 22%
- Foundation models and inference now absorb roughly 22% of enterprise AI budgets, down from about 38% in 2024. The money moved to retrieval, integration, evaluation and the people who tune them.Source: State of Agentic AI in the Enterprise 2026 →
- 60–75%
- Cheap-first cascade routing — attempt the cheapest capable model, escalate on a confidence check — moves 60% to 75% of traffic to the cheap tier with no measurable quality regression.Source: Enterprise LLM Cost & TCO Benchmarks 2026 →
External references
- OWASP — Top 10 for LLM Applications (2025)The threat list our prompt-injection, output-handling and tool-permission guardrails map to.
- NIST — AI Risk Management Framework (AI RMF 1.0) (2023)The govern / map / measure / manage structure Pronix uses to organise AI controls.