Retrieval Is Not Enough — Federico Bottino

Why Organizational AI Needs Epistemic Infrastructure

Federico Bottino, Carlo Ferrero, Nicholas Dosio, Pierfrancesco Beneventano

Paper, Preprint, arXiv preprint (cs.AI), 2026

Abstract

Organizational AI systems need epistemic structure beyond retrieval capabilities. We present OIDA, a framework that represents organizational knowledge as typed objects with epistemic properties, commitment strength, and contradiction status. A key innovation is QUESTION-as-modeled-ignorance, which surfaces organizational unknowns. Experimental evaluation uses an Epistemic Quality Score methodology; OIDA achieves 0.530 EQS with 3,868 tokens versus 0.848 for a full-context baseline using 108,687 tokens. The QUESTION mechanism shows statistical significance with Fisher p=0.0325.

K-score trajectories over 28 days under stationary inputs for five epistemic classes: QUESTION rises from 0.5 to 0.556, OBSERVATION decays from 0.5 to 0.435, DECISION near-stable, EVIDENCE and HYPOTHESIS in between. — Figure 1 — K-score dynamics over 28 days (paper Theorem 1 / Figure 2). With identical initial conditions, QUESTION KOs gain urgency from the first update while OBSERVATION decays. What is unknown ends up outranking what is stale.

EQS sub-score comparison from Table 5 of the OIDA paper: Minerva (OIDA RAG, 3868 tokens) vs Cowork (full-context baseline, 108687 tokens) on ECA, CP, CR, EC, DE and composite EQS, plus QUESTION declaration callout 10/10 vs 5/10 (Fisher p=0.0325). — Figure 2 — EQS sub-score breakdown (paper Table 5, n=10 response pairs). Composite EQS 0.530 vs 0.848 at a 28.1× token-budget gap. The unconfounded architectural signal is the QUESTION declaration rate: 10/10 for OIDA vs 5/10 for the baseline.

Log-log plot of token budget to reach context sufficiency CS@8 ≥ 0.8 across corpus sizes 30 to 3M docs, for BM25, Dense, Hybrid, OIDA, Whitelist. OIDA stays near 1,000–1,500 tokens; BM25 / Dense / Hybrid blow past the 16K budget by 3K–30K docs. — Figure 3 — OIDA Bench v2 (forthcoming). Token budget needed to reach CS@8 ≥ 0.8, by corpus size. OIDA stays flat near 1,000–1,500 tokens regardless of how big the corpus gets; BM25, Dense and Hybrid scale poorly and hit the never-reached zone (≥ 16K tokens) by 3K–30K documents.

Horizontal bar chart of token budget to reach CS ≥ 0.5 on the clean_big corpus (30K docs): BM25 ~1684 tok, Dense not reached, Hybrid ~1684 tok, OIDA ~842 tok, Whitelist ~900 tok. — Figure 4 — OIDA Bench v2 (forthcoming). Budget at the clean_big corpus (30K docs), interpolated from the multi-budget sweep. OIDA reaches CS ≥ 0.5 with ~842 tokens — about 2× more efficient than BM25 or Hybrid (~1,684 tok). Dense never reaches the 0.5 threshold at any tested budget.