Fan Out or Relay? Ownership-Aware Routing for LLM Agents Querying Siloed Tables

Zhexi Feng

cs.CLOct 13, 2026

Fan Out or Relay? Ownership-Aware Routing for LLM Agents Querying Siloed Tables

Authors: Zhexi Feng

Organizations: Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA

Abstract

Inside organizations, a question's data often sit with several owners, who query their own tables but never hand them over. An LLM coordinator can fan out, sending the question to every owner at once, or relay, querying owners in turn and reusing earlier rows. We show that neither is safe in advance, because data ownership decides which one is right. Across thirteen settings on PeopleJoin and BIRD with three model families, fan-out is more accurate in twelve on questions one owner can answer, yet answers at most 4.3% of those joining two owners' tables. The flip follows ownership, not query shape: on BIRD two-table joins, fan-out answers 32-44% when one owner holds both and 1-4% otherwise. Relay wins by conditioning on returned rows, and hiding them from an otherwise identical planner cuts two-owner accuracy from 23.2% to 5.1%. Since ownership is public, we propose Ownership-Aware Routing (OAR), which drafts a schema-only SQL query, counts the owners whose tables it joins, and routes the question before any private row is read. In ten settings OAR is never significantly less accurate than the best fixed protocol, and beats every fixed protocol on PeopleJoin, by up to 9.3 points on held-out organizations.

Figures & tables

Figure 1: (1) A coordinator answers a question over tables held by different owners, who publish their schemas but keep their rows. (2) When the question joins tables of two owners, fan-out fails because Alice’s department ids never reach Bob, while relay places them in its query to Bob. (3) OAR drafts one SQL query over the public schema, counts the owners whose tables it joins (its owner cover

\kappa

, Equation 1 ), and routes the question before any private row is read.

Pool	DBs	Qs	1-own.	Split	2-own.	Models
PJ-8a	8	96	41	2	36	DS
PJ-8b	8	494	275	14	138	DS, So
PJ-7	7	511	203	45	134	DS, So, Qw
PJ-Unseen	108	300	147	29	71	DS, Qw
BIRD	11	500	130	–	293	DS, So, Qw
BIRD-Unseen	11	300	68	–	171	DS, Qw

Table 1: Evaluation pools. Single-owner, row-split and two-owner counts use the reference cover

\kappa

(Section 2 ). The other questions need three or more owners, are unanswerable or have references whose tables could not be resolved. DS, So, Qw: DeepSeek, Sonnet, Qwen.

Figure 2: Accuracy of fan-out and relay on single-owner questions (left) and two-owner questions (right) in all thirteen settings. Diamonds mark OAR in the ten settings where it runs. Fan-out leads on the left and collapses on the right, while OAR stays close to fan-out on the left and to relay on the right.

Setting	FO	RL	FO	RL	Diff.
	One owner		Two owners
BIRD, DS	36.4	25.0	4.2	25.9	+33.0
BIRD, So	31.8	27.3	3.0	28.9	+30.4
BIRD, Qw	36.4	27.3	2.7	30.0	+36.5
BIRD-Uns., DS	44.4	22.2	1.3	23.9	+44.9
BIRD-Uns., Qw	38.9	38.9	3.1	34.6	+31.4

Table 2: Accuracy (%) on questions whose reference SQL joins exactly two tables, by whether the hash-based partition gives both tables to one owner (44 questions on BIRD, 18 on BIRD-Unseen) or to two (263 and 159). FO: fan-out, RL: relay. Diff.: fan-out’s lead with one owner minus its lead with two, in points, with every 95% interval above zero.

Figure 3: Two-owner accuracy in the mechanism experiments. The first two bars show the Relay+ planner without its key-passing instruction, with the returned rows visible or hidden. The planned variant writes all of relay’s queries before any row returns. With Sonnet on PJ-8b the comparisons point the same way with smaller gaps.

	Fixed protocols			Other routers			Ownership routing
Setting	Fan-out	Relay	Relay+	Self	Ask	Difficulty	OAR	OAR+
PJ-7, DeepSeek	39.5	36.9	38.1	38.6	39.7	–	42.0 †	41.4
PJ-7, Sonnet	39.3	31.1	–	–	–	–	42.7 †	–
PJ-7, Qwen	41.3	41.5	–	42.3	43.4	–	44.2 †	–
PJ-Unseen, DeepSeek	52.7	54.0	53.0	60.9	58.3	–	63.3 †	61.3
PJ-Unseen, Qwen	55.7	57.7	56.7	62.7	60.0	–	65.0 †	65.0

Table 3: Accuracy (%) of the fixed protocols and the routers. Each router picks the saved fan-out or relay run of a question by the model’s choice (Self), by the owners the model says the question needs (Ask), by BIRD’s gold difficulty labels (Difficulty) or by the draft’s owner cover (OAR). Bold marks the highest accuracy in each row, and † marks OAR when its 95% interval against the best fixed protocol lies above zero (Appendix C ).

Appendix figures & tables12 assets

Supplementary material from the paper’s appendix.

Appendix

	Single-owner			Row-split			Two-owner			Unanswerable
Setting	FO	RL	OAR	FO	RL	OAR	FO	RL	OAR	FO	RL	OAR
PJ-7, DeepSeek	46.3	41.6	45.8	22.2	12.2	22.2	0.0	11.6	10.1	92.5	78.3	92.5
PJ-7, Sonnet	45.3	40.9	45.3	20.0	17.8	20.0	2.2	14.2	12.7	91.5	41.5	90.6
PJ-7, Qwen	51.2	45.8	50.7	22.2	13.3	22.2	0.0	12.7	11.9	91.5	90.6	91.5
PJ-Unseen, DeepSeek	77.6	67.3	76.2	55.2	10.3	51.7	1.4	47.9	47.9	75.0	58.3	66.7
PJ-Unseen, Qwen	80.3	74.1	80.3	69.0	24.1	69.0	1.4	38.0	38.0	75.0	72.2	72.2

Appendix

Table 4: Accuracy (%) by reference owner cover. FO: fan-out, RL: relay. OAR follows fan-out on single-owner, row-split and unanswerable questions and relay on two-owner questions. BIRD has no row-split or unanswerable questions. On PJ-Unseen the last group also contains four questions whose reference tables could not be resolved.

	Single-owner					Two-owner					Three or more owners
Setting	FO	RL	RL+	OAR	OAR+	FO	RL	RL+	OAR	OAR+	FO	RL	RL+	OAR	OAR+
PJ-7, DS	46.3	41.6	41.9	45.8	46.1	0.0	11.6	8.2	10.1	7.1	0.0	0.0	0.0	0.0	0.0
PJ-7, So	45.3	40.9	–	45.3	–	2.2	14.2	–	12.7	–	0.0	21.7	–	17.4	–
PJ-7, Qw	51.2	45.8	–	50.7	–	0.0	12.7	–	11.9	–	0.0	0.0	–	0.0	–
PJ-Unseen, DS	77.6	67.3	68.7	76.2	75.5	1.4	47.9	40.8	47.9	40.8	0.0	29.4	17.6	29.4	17.6
PJ-Unseen, Qw	80.3	74.1	73.5	80.3	80.3	1.4	38.0	38.0	38.0	38.0	5.9	23.5	17.6	23.5	17.6

Appendix

Table 5: Accuracy (%) by reference owner cover, including Relay+ and OAR+. FO: fan-out, RL: relay, RL+: Relay+. Single-owner questions exclude the row-split questions of Table 4 . Three-or-more groups hold 23 (PJ-7), 17 (PJ-Unseen), 69 (BIRD) and 41 (BIRD-Unseen) questions.

Setting	Relay	Relay+
PJ-8a, DS	+24.0 [5.5, 43.1]	–
PJ-8b, DS	+37.2 [28.1, 46.3]	–
PJ-8b, So	+33.3 [23.5, 43.5]	–
PJ-7, DS	+16.2 [8.7, 24.6]	+12.6 [5.6, 20.2]
PJ-7, So	+16.4 [8.0, 25.5]	–
PJ-7, Qw	+18.1 [10.9, 25.8]	–

Appendix

Table 6: Interaction between protocol and ownership in points: the advantage of relay (or Relay+) over fan-out on two-owner questions minus its advantage on single-owner questions, with 95% intervals.

	Fan-out				Relay
Setting	Correct	Abst.	Wrong	Stop.	Correct	Abst.	Key	No key	Stop.
PJ-7, DeepSeek	0.0	80.6	19.4	0.0	11.9	42.5	23.1	16.4	6.0
PJ-7, Qwen	0.0	81.3	17.9	0.7	12.7	54.5	20.1	12.7	0.0
PJ-Unseen, DeepSeek	1.4	90.1	8.5	0.0	47.9	19.7	18.3	8.5	5.6
BIRD, DeepSeek	4.1	78.2	16.4	1.4	25.3	18.4	28.7	4.8	22.9
BIRD, Qwen	3.1	77.8	18.1	1.0	28.7	27.0	32.1	4.8	7.5

Appendix

Table 7: Outcomes on two-owner questions (% of questions, first run). Abst.: the receiver declares the question unanswerable or returns no rows. Wrong: wrong rows. Key and No key: wrong rows after relay passed a key or without one. Stop.: the run ends early, for relay mostly because its provenance reserve is exhausted.

Q: What is the amount of the funds that the Vice President received? (BIRD, student_club )
Step 1 , owner of member : SELECT member_id FROM member WHERE position = 'Vice President' LIMIT 5 $\rightarrow$ recD078PnS3x2doBe
Step 2 , owner of income : SELECT amount FROM income WHERE link_to_member = 'recD078PnS3x2doBe' LIMIT 5 $\rightarrow$ 50
Relay answers 50, which is correct. Under fan-out each owner answers alone, and the receiver abstains.

Appendix

Table 8: A relay run with DeepSeek in which the member id returned by one owner becomes the filter of the query to the next owner.

Setting	Runs	Key (%)	key	no key	Share (%)
			Accuracy (%)
PJ-7, DS	268	52.6	12.1	11.0	54.8
PJ-7, So	134	65.7	15.9	10.9	73.7
PJ-7, Qw	134	44.8	15.0	10.8	52.9
PJ-Uns., DS	71	74.6	58.5	16.7	91.2
PJ-Uns., Qw	71	64.8	50.0	16.0	85.2

Appendix

Table 9: Key passing in relay runs on two-owner questions. Key: share of runs in which a later query contains a literal value that a different owner returned earlier. Share: fraction of the correct runs that passed a key.

Setting	Qs	FO	RL	Qs	FO	RL
	At most 20 rows			More than 20
PJ-8a, DS	34	61.8	55.9	7	14.3	0.0
PJ-8b, DS	218	59.9	49.5	57	33.3	0.0
PJ-8b, So	218	52.8	55.0	57	21.1	1.8
PJ-7, DS	173	48.6	48.8	30	33.3	0.0
PJ-7, So	173	46.8	47.4	30	36.7	3.3

Appendix

Table 10: Single-owner accuracy (%) by the number of rows in the reference answer. Relay limits each step to 20 rows.

Setting	OAR $-$ FO	OAR $-$ RL	OAR $-$ best	OAR+ $-$ RL+	OAR+ $-$ OAR
PJ-7, DeepSeek	+2.4 [1.0, 4.0]	+5.1 [2.3, 7.9]	+2.4 [1.0, 4.0]	+3.3 [0.9, 5.9]	$-$ 0.6 [ $-$ 1.5, 0.3]
PJ-7, Sonnet	+3.3 [1.4, 5.3]	+11.5 [7.8, 15.3]	+3.3 [1.4, 5.3]	–	–
PJ-7, Qwen	+2.9 [1.4, 4.5]	+2.7 [0.6, 5.1]	+2.7 [0.6, 5.1]	–	–
PJ-Unseen, DeepSeek	+10.7 [6.3, 15.0]	+9.3 [5.0, 13.7]	+9.3 [5.0, 13.7]	+8.3 [4.0, 12.7]	$-$ 2.0 [ $-$ 4.7, 0.3]
PJ-Unseen, Qwen	+9.3 [5.7, 13.0]	+7.3 [3.0, 11.7]	+7.3 [3.0, 11.7]	+8.3 [4.0, 12.7]	+0.0 [ $-$ 2.0, 2.0]
BIRD, DeepSeek	+14.3 [11.1, 17.6]	+3.6 [1.4, 5.9]	$-$ 1.5 [ $-$ 4.4, 1.4]	+1.3 [ $-$ 0.7, 3.3]	+2.8 [0.7, 4.9]

Appendix

Table 11: Paired differences in points with 95% intervals. FO: fan-out, RL: relay, RL+: Relay+. “Best” is the most accurate fixed protocol of the setting, including Relay+ where it runs.

Figure 4: Expected accuracy as the share of two-owner questions varies, obtained by reweighting the measured single-owner and two-owner accuracies. OAR stays near the better of fan-out and relay for every mix and exceeds both at intermediate mixes.

	Single-owner			Two-owner			All questions
Setting	FO	RL	OAR	FO	RL	OAR	FO	RL	OAR
PJ-7, DeepSeek	50.8	47.1	49.5	1.1	13.1	12.4	43.0	40.9	45.7
PJ-7, Sonnet	49.5	42.4	49.1	3.2	18.7	17.7	42.1	33.6	46.4
PJ-7, Qwen	53.1	51.2	52.6	1.2	15.2	15.1	43.3	45.9	47.1
PJ-Unseen, DeepSeek	80.0	69.0	78.6	3.3	54.7	52.5	54.9	59.8	67.4
PJ-Unseen, Qwen	81.0	74.9	81.0	3.3	45.6	44.6	57.4	62.7	68.2

Appendix

Table 12: Row-level F1 (%), which gives partial credit for overlapping rows. FO: fan-out, RL: relay. Bold marks the highest F1 over all questions in each row.

	Draft		Accuracy (%)
Setting	Prec.	Rec.	Oracle	OAR	Table	JOIN
PJ-7, DS	94.9	65.6	42.6	42.0	41.1	40.6
PJ-7, So	96.9	59.2	43.4	42.7	43.1	42.9
PJ-7, Qw	94.5	66.2	44.6	44.2	43.8	43.8
PJ-Uns., DS	87.9	90.9	65.3	63.3	–	–
PJ-Uns., Qw	93.7	84.1	65.3	65.0	–	–

Appendix

Table 13: How the draft routes. Precision and recall of the draft’s multi-owner (

\kappa\geq 2

) prediction against the reference cover. Oracle routes by the reference cover with the same relay branch as OAR. Table and JOIN route the same draft on its table count or on the presence of a JOIN.

Setting	Best	OAR	8B	$\Delta$ [95% CI]	Rec.
PJ-7, DS	39.5	42.0	39.6	+0.1 [ $-$ 1.8, 2.0]	61.1
PJ-7, So	39.3	42.7	38.6	$-$ 0.8 [ $-$ 3.3, 1.6]	61.1
PJ-7, Qw	41.5	44.2	43.6	+2.2 [0.0, 4.3]	61.1
PJ-Uns., DS	54.0	63.3	60.3	+6.3 [2.0, 11.0]	78.4
PJ-Uns., Qw	57.7	65.0	60.7	+3.0 [ $-$ 1.3, 7.3]	78.4
BIRD, DS	30.3	28.8	26.5	$-$ 3.8 [ $-$ 6.8, $-$ 0.7]	67.7

Appendix

Table 14: OAR with drafts from Llama-3.1-8B (8B), with the executors of each setting. Best: the most accurate fixed protocol, as in Table 3 . OAR: drafts from the executing model.

\Delta

: 8B minus Best in points. Rec.: the share of multi-owner questions that the 8B draft recognizes, the same for every executor of a pool.

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Business Truth, not SQL Accuracy: A Rule-Gated 7B Analytics Agent Outperforms a Direct-Prompted 32B Baseline

Morris Lee

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Open paper AskPDF arXiv

LLM analytics agents are evaluated on SQL syntax accuracy, but production failures look different: questions with two valid business definitions, questions the warehouse cannot answer, deprecated columns after a schema change, and queries that execute successfully while returning the wrong business number. No execution-match metric can score them. This paper introduces WarehouseReliabilityBench, 400 frozen tasks over two synthetic warehouses in which roughly half the correct responses are a clarification, an abstention or a refusal, with pinned denominators and a pre-registered paired bootstrap fixing each claim verb before the numbers existed. QueryProof, a 7B agent, uses rules derived from a semantic layer and physical catalog to determine its behaviour, and gates every answer on deterministic post-execution checks. On an 80-task synthetic test split evaluated once, QueryProof outperforms a direct-prompted 32B baseline by +0.237 [+0.112, +0.375] Business Truth Rate at 71.0% lower cost per correct answer; against a cost-matched few-shot baseline the accuracy gain holds but the cost difference does not resolve. This compares systems rather than model sizes: the 32B baseline receives none of the scaffolding. False success falls from 0.754 to 0.351 of returned answers, and no wrong number was returned on an answerable task (0 of 24), though 13 answers went to questions requiring clarification or abstention. Removing the routing layer changes little (0.562 against 0.537), so the result does not depend on escalation. Routing tuned on validation over-abstains on test, and the fitted confidence model loses to the heuristic it replaced. Resampling template families rather than tasks widens both accuracy intervals to include zero, so the effect's direction is better supported than its magnitude. The gain tracks the deterministic layer, though no component ablation was run.

Abstract

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