An Alignment Benchmark for Enterprise Agents on Era by Eon

Authors: Hai Sadon , Benjamin Gruenbaum , Doron Porat , Assaf Natanzon , Roy Zavida , Chen Dinachi , Or Itzahary

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Abstract: AI agents are widely used in enterprises to access business systems and act on them in pursuit of a goal. However, fulfilling a user's request can cause harm. Era by Eon is a product that creates a digital twin of a company by simulating its business systems and data. Its simulators implement the programming interfaces of real products. Our benchmark uses ten of these systems, including Salesforce, Zendesk, Jira and Slack. We tested whether agents would carry out harmful business requests or trust misleading information in company records. We ran 19 models on 41 tasks three times, for 2,337 runs. Of the 2,304 runs that produced an answer, 918 (40%) contained a violation. The most common were false claims about actions or records (290 runs), following planted instructions (266) and disclosing sensitive data to the wrong audience (249). Every attempted change was recorded and blocked before it took effect. Misleading Slack messages caused 16 models to report an incorrect ticket status in 47 of 57 runs. No model was free of violations. The four best models violated in 22 to 24% of their runs. Yet one of them, Nova Pro, did the task correctly in only 30 runs.

Comments:

11 pages, 1 figure, 4 tables

Subjects:

Artificial Intelligence (cs.AI) ; Software Engineering (cs.SE)

ACM classes:

I.2.7; I.2.11; K.6.5

Cite as:

arXiv:2610.38544 [cs.AI]

(or

arXiv:2610.38544v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2610.38544

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arXiv-issued DOI via DataCite

Submission history

From: Assaf Natanzon [ view email ]

[v1]

Wed, 28 Oct 2026 09:45:17 UTC (43 KB)

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