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New CRM-Agent-Bench benchmarks enterprise language agents

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced CRM-Agent-Bench, a new benchmark designed to evaluate language agents in stateful enterprise environments. This benchmark assesses agents on four key facets: outcome, trajectory, operational viability, and policy compliance, using customer relationship management (CRM) tasks as a testbed. The benchmark comprises 555 multi-turn tasks across nine business domains, each with an executable contract that agents must strictly adhere to for success. Initial evaluations of sixteen systems showed a strict success rate between 64.32% and 83.60%, with significant divergence in cost and reliability among the top performers. AI

IMPACT This benchmark could accelerate the development and deployment of more reliable and compliant AI agents in enterprise settings.

RANK_REASON The cluster contains an academic paper introducing a new benchmark for evaluating AI agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New CRM-Agent-Bench benchmarks enterprise language agents

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The cluster contains an academic paper introducing a new benchmark for evaluating AI agents. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Monojit Banerjee, Zhujun Lan, Defu Cao ·

    CRM-Agent-Bench: Benchmarking Tool-Using Agents in Stateful Enterprise Environments

    arXiv:2610.32004v1 Announce Type: cross Abstract: Deploying language agents in real applications demands more than the right answer: an agent must execute a multi-step business process correctly, follow domain-specific rules, and interact with a user across a dialogue, where the …

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