ReevolSignal

Vidrios San Miguel Coop V

ES · Environmental Protection · Est. 1986 · vsanmiguel.com

Last refreshed 2026-06-01

35Dark Signal

Based on 3 AI engines across 1 buyer language.

AI Readiness pillars

How Vidrios San Miguel Coop V performs against the three pillars buyers care about when sourcing via AI.

AI Knowledge20 / 100

Weight 40% · Do multiple AI engines recognise you and tell a consistent story

AI Recommendation60 / 100

Weight 30% · When buyers ask AI to source in your niche, do you come up

AI Verdict30 / 100

Weight 30% · How AI engines rate you on quality, reliability, pricing

What AI says

AI引擎对Vidrios San Miguel Coop V的信息掌握不完整,该公司是西班牙的一家环保供应商。在近期查询中,该公司综合得分为100分中的56分(弱信号),其中最强维度为身份与存在感,得分为100分中的80分,最弱维度为买家信任,得分为100分中的0分。在测试的3个AI引擎(Claude Haiku、gemini-2.5-flash、deepseek-chat)中,有2个针对公司身份、采购及信任相关提示返回了实质性信息。AI识别出的产品包括玻璃制品。AI回复中未涉及任何认证或第三方验证信息,这导致买家信任维度得分仅为100分中的0分,AI推荐率为100分中的70分。最大的改进机会在于买家信任维度,下方的改进路线图按预期得分提升幅度排列了供应商可执行的具体行动。

AI engine breakdown

One row per AI engine. Aggregates identity, sourcing, trust, and verdict queries.

AI EngineFoundSentimentRatingProducts mentionedCertifications
Claude Haiku0 / 4not foundNoneNone
Gemini 2.5 Flash1 / 4neutralglass productsNone
DeepSeek2 / 4neutralglass productsNone

Improvement Roadmap

Concrete actions to lift this supplier's Signal Score, ranked by impact. Generated from the latest audit.

  1. 1

    Publish third-party certifications and compliance documentation

    +28 pts

    Create a dedicated Certifications page listing ISO, environmental, or industry-specific certifications with scanned proof documents. This directly addresses AI's inability to verify legitimacy and certification status, which is the primary blocker to buyer trust scoring.

    Buyer Trust SignalsMedium effort

  2. 2

    Build structured product catalog with specifications and applications

    +18 pts

    Document each glass product type with technical specs, dimensions, certifications, and use cases in a publicly accessible format (PDF catalog or web pages). AI systems currently only recognize 'glass products' generically; clarity on product range and standards will improve recommendation likelihood.

    Product ClarityMedium effort

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