Google DeepMind

业务场景：客服坐席辅助

Google Cloud's public case names Gemini 1.5 Pro in Gelato's engineering-support ticket triage and customer-support error categorization. It reports 120 hours of weekly manual tasks saved and ticket-assignment accuracy increasing from 60% to 90%; Gemini automatically assigns tickets to the responsible engineering team. Gelato also describes instant error classification in customer-support systems.

ROI：公开投入、持续成本、收益或测量周期不足，未计算。

边界：Vendor-authored Google Cloud case; the reported 120 hours, accuracy figures and support-system result are not isolated from Vertex AI, data preparation, workflow integration or human review. The page does not publish a dated API model ID, sample, evaluation method, measurement period, cost, quality beyond assignment accuracy or independent validation. The separate plan to use Gemini 2.0 for image-based product quality is not bound to this Gemini 1.5 Pro case.

业务场景：客服坐席辅助

Hershey Entertainment & Resorts uses Google Cloud Customer Engagement Suite, Conversational Agents, Vertex AI, Gemini and connected enterprise systems to automate guest and employee support. The public case reports chatbot launch in less than 40 hours, more than 25% of employee call-off requests automated, 50%+ of password-reset calls managed, and eight hours of employee work saved per day.

ROI：公开投入、持续成本、收益或测量周期不足，未计算。

边界：Vendor-authored Google Cloud case; no Gemini model/version is named, so this case remains organization-level. The contribution of Gemini versus Dialogflow/Conversational Agents, BigQuery, webhooks and workflow integrations is not isolated. Sample, period, cost, quality, escalation and independent validation are not disclosed.

业务场景：销售与营销内容

Square Yards uses Gemini Enterprise Agent Platform and Gemini APIs with other Google Cloud services to run SuperAgent Pro, a multilingual conversational voice engine. The public case reports 200,000 automated calls per day, sub-700ms conversational response latency, 12+ Indian languages and 10 billion Gemini AI tokens consumed per month.

ROI：公开投入、持续成本、收益或测量周期不足，未计算。

边界：Vendor-authored Google Cloud case; no Gemini model/version or API model ID is named, so this case remains organization-level. The reported scale and latency are not an independent productivity or ROI evaluation; call outcomes, conversion quality, human handoff rate, cost, measurement period and model-specific contribution are not disclosed.