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AI Visibility Scorecard
andovar.com · Technology
Somewhat visible. AI bots can read International AI Data Solutions for Multilingual AI Data Training, but it is missing the structured signals that push citation rate above competitors.
AI engines read this profile 5 times
Meta AI · Claude · Apple Intelligence
#256,956 of 2,655,352 in Technology for AI visibility
5.9
/10
AEO Score
from our crawl and measurement
International AI Data Solutions for Multilingual AI Data Training describes itself simply: "Providing text data, voice data, speech data, video data, image data and localization in over 200 languages, we ensure your language models are optimized for global audiences." Its AI visibility score is 5.9 out of 10: the engines can find it, but they do not have much to hold on to.
Our crawl found structured data on the page (CreativeWorkSeries, FAQPage). It is missing an llms.txt file, a sitemap and a heading structure that lays out what it offers.
AI crawlers have visited once in our tracking, including ClaudeBot (Anthropic).
Higher is better · 0-10
Structured Data
6
Organization / LocalBusiness JSON-LD that AI can read.
Content Structure
7
Clear headings and answer-style content.
Entity Clarity
3
How clearly your brand identity reads to AI.
E-E-A-T Signals
Experience, Expertise, Authority, Trust
6
Experience, Expertise, Authority, Trust markers.
Technical AEO
4
robots.txt, llms.txt, and AI-bot crawl access.
AI Discoverability
4
Sitemaps and entity links AI can follow.
How the web signals your brand to AI
Backlinks
10
Inbound links from other sites.
Domain Authority
4
Established authority for your domain.
Reference Presence
0
Not in AI knowledge graphs yet.
News & Press
0
No press coverage found yet.
Community
1
Forum and community discussion.
Social Mentions
0
No social discussion found yet.
Your AEO score measures whether AI search engines - ChatGPT, Claude, Perplexity, Gemini - can actually read your site and cite it in answers. Roughly two-thirds of sites are invisible to them. At 5.9/10, International AI Data Solutions for Multilingual AI Data Training has a working base to build on - fixable, and the signals above are where to start.
What types of AI training data services does Andovar provide?
Andovar provides end-to-end AI training data services, including speech training data for AI, text data, monolingual corpora as training data for AI, image and video data, and multilingual data annotation. All training data is designed to support real-world AI development and deployment.
Who are Andovar’s AI training data services designed for?
We offer tailored training data for AI, for startups and enterprises across a wide range of industries, leveraging our expertise to deliver customised datasets aligned with specific technical, linguistic, and business objectives.
How much do AI training data services cost?
The cost of AI training data services depends on factors such as data type, language coverage, volume, annotation requirements, and delivery timelines. Andovar provides transparent, project-based pricing aligned with your technical requirements and use case.
How quickly can you deliver AI training data?
Delivery timelines vary based on dataset complexity and scale. Smaller or existing datasets can often be delivered quickly, while large-scale or highly customized AI training data projects may require additional time to ensure quality, diversity, and compliance.
Can I see samples of your AI training data?
Yes. We can provide sample datasets or data excerpts so you can evaluate structure, quality, and suitability before committing to a full AI training data services engagement.
What makes your data “custom data”?
Custom data is built specifically for your AI use case. Andovar’s custom AI training data is defined by your target languages, demographics, environments, domains, and model objectives—ensuring the data reflects real users rather than generic assumptions.
Do your AI training datasets come labeled?
Yes. We offer fully labeled and annotated AI training datasets, including transcription, classification, tagging, and validation. Annotation workflows are designed to align with your model architecture and performance goals.
What is better: off-the-shelf data or custom-made AI training data?
Off-the-shelf data can be useful for early experimentation. However, custom AI training data is often essential for production-ready models, as it reflects real-world conditions, target users, and domain-specific requirements more accurately.
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Scored by Engagemii on July 31, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/andovar
Cite this score: Engagemii (2026). "AEO Score for International AI Data Solutions for Multilingual AI Data Training." Retrieved from https://engagemii.com/aeo/brands/andovar
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