URBASOLAR

What AI says

AI engines have a partial picture of URBASOLAR, a Renewable Energy supplier in fr. Across recent queries the company scored 45 out of 100 (Weak Signal), with the strongest dimension being Product Clarity at 80 out of 100 and the weakest Digital Footprint at 20 out of 100. One AI engine (out of 3 tested: GPT-4o mini, Claude Haiku, deepseek-chat) returned substantive information about the company across identity, sourcing, and trust prompts. Products surfaced by AI include photovoltaic power plants, solar solutions, renewable energy projects. No certifications or third-party validations surfaced in AI responses, which limits the Buyer Trust dimension at 45 out of 100 and the AI Recommendation Rate at 30 out of 100. The biggest opportunity for improvement is the Digital Footprint dimension; the Improvement Roadmap below lists concrete supplier-executable actions ranked by expected score uplift.

AI engine breakdown

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

Improvement Roadmap

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

1. 1

   Publish structured schema markup for company and solar products

   +18 pts

   Add JSON-LD schema.org markup to homepage (Organization, LocalBusiness, Product types for photovoltaic systems) to improve AI engine crawl clarity and entity recognition. This directly increases discoverability by search indexes and LLM training pipelines, lifting your found-by-name rate from 1/3 toward 3/3.

   Digital Footprint · Low effort

2. 2

   Document and display ISO 9001 or equivalent quality certification

   +16 pts

   Obtain and publish scans of relevant certifications (ISO 9001, ISO 45001, or solar-specific standards like IEC 61730) in an easy-access Certifications page. Certifications are a primary trust signal for B2B renewable energy buyers and currently absent from AI knowledge.

   Buyer Trust Signals · Medium effort

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