{"id":59880,"date":"2026-03-11T10:01:21","date_gmt":"2026-03-11T10:01:21","guid":{"rendered":"https:\/\/dmi5324.dotlogicstest.com\/?post_type=case-study&p=59880"},"modified":"2026-03-11T12:19:30","modified_gmt":"2026-03-11T12:19:30","slug":"case-studyllm-evaluation","status":"publish","type":"case-study","link":"https:\/\/dmi5324.dotlogicstest.com\/pl\/case-study\/case-studyllm-evaluation\/","title":{"rendered":"LLM Evaluation at Scale for a Leading AI Research Organization"},"content":{"rendered":"\t\t
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L<\/span>LM<\/span>\u00a0Evaluation at Scale for a Leading AI Research Organization<\/span><\/span>\u00a0<\/span><\/h2>

To conduct LLM performance evaluations to assess output quality across models in multiple languages<\/span>\u00a0and modalities<\/span>, the client partnered with\u00a0<\/span>DATAmundi<\/span>. The result was a successful, ongoing partnership with new LLMs launched and volumes continuing to grow<\/span><\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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The Client<\/span><\/b>\u00a0<\/span><\/h2>

A leading AI research organi<\/span>z<\/span>ation within a Fortune 100 technology company conducts ongoing large language model<\/span>\u00a0(LLM)<\/span>\u00a0performance evaluations to assess output quality across multiple models<\/span>\u00a0and\u00a0<\/span>configurations.<\/span><\/span>\u00a0<\/span><\/p><\/div>

Their AI team\u00a0<\/span>operates<\/span>\u00a0without fixed schedules. Studies are triggered whenever a new model is released\u00a0<\/span>on<\/span>\u00a0the market. This requires a partner capable of delivering high-quality\u00a0<\/span>multimodal\u00a0<\/span>human evaluation on demand, often without advance notice.<\/span><\/span>\u00a0<\/span><\/p><\/div>

DATAmundi<\/span>\u00a0has supported this LLM performance evaluation project for 1.5 years and<\/span>\u00a0growing –<\/span>\u00a0as part of a multi-year engagement with the client.<\/span><\/span>\u00a0<\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The Challenge<\/span><\/b>\u00a0<\/span><\/h2>

The client’s work required\u00a0<\/span>spontaneous delivery without advance notice.<\/span>\u00a0Each new LLM launch triggered evaluation studies with volumes fluctuating dramatically week to week, from 100 utterances to 10,000+. The work expanded from English-only to\u00a0<\/span>five language variants<\/span><\/span>\u00a0<\/span>(English US\/UK\/Canadian, Spanish Mexican\/US, and others), and from evaluation to include\u00a0<\/span>response collection<\/span><\/span><\/a>\u00a0across precise technical specifications.<\/span>\u00a0<\/span><\/p><\/div>

The\u00a0<\/span>evaluation<\/span><\/span><\/a>\u00a0itself demanded<\/span>\u00a0<\/span>a three-step assessment: response validity (does the answer address the question), accuracy (how complete and\u00a0<\/span>accurate<\/span>\u00a0it is), and\u00a0<\/span>fact-checking<\/span>\u00a0(verification of sources and regional appropriateness). The same query set went to five different annotators for majority consensus, requiring consistency across the entire annotation team. Any error in model version, response mode (text\/voice\/image), or regional settings would invalidate study results.<\/span><\/span>\u00a0<\/span><\/p>

Our Approach<\/h2>

DATAmundi\u00a0built a standing infrastructure designed for spontaneity and quality. We\u00a0maintained<\/span>\u00a0<\/span><\/b>dedicated teams of 10-12 specialized annotators per<\/span>\u00a0<\/span><\/b>language<\/span>\u00a0<\/span><\/b>who worked exclusively on this\u00a0project. Each underwent comprehensive training on the three-step evaluation\u00a0methodology, with our QC Lead simplifying complex technical guidelines into accessible modules.<\/span>\u00a0<\/span><\/p>

We\u00a0established\u00a024\/7 project management coverage across time zones. As one PM logged off, another took over, ensuring annotators always had immediate support for guideline questions or technical clarifications. Our standing pool of trained annotators allowed rapid scaling when volumes increased, with new annotators completing the same rigorous training before starting work.<\/span>\u00a0<\/span><\/p>

DATAmundi’s\u00a0<\/span>AIDA Hub platform<\/span><\/a>\u00a0managed complex workflow requirements across different evaluation criteria, response modes, and language variants. Throughout the partnership, the client\u00a0maintained\u00a0a collaborative approach, working with us to refine guidelines rather than simply flagging issues, allowing continuous quality improvement.<\/span>\u00a0<\/span><\/p>

The Results<\/span><\/b>\u00a0<\/span><\/h2>

The partnership has grown consistently with the client continuously increasing volumes. The rigorous three-step evaluation process was\u00a0maintained\u00a0consistently across all language variants and response modes (text, voice, and image).<\/span>\u00a0<\/span><\/p>

As the client expanded their evaluation scope across models, languages, and response formats,\u00a0DATAmundi\u2019s\u00a0infrastructure enabled rapid scaling without disrupting delivery timelines. Dedicated annotator teams, majority-consensus review, and 24\/7 project management support ensured that evaluation quality remained consistent even as workloads fluctuated significantly between studies.<\/span>\u00a0<\/span><\/p>

The following metrics summarize the scale and structure of the evaluation work delivered during the partnership.<\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The Business Impact<\/span><\/b>\u00a0<\/span><\/h2>

The client received a reliable, expert-level\u00a0<\/span>LLM evaluation<\/span><\/a>\u00a0that supported their market research objectives.\u00a0DATAmundi’s\u00a0ability to deliver on spontaneous requests enabled their AI team to respond quickly to market developments.\u00a0<\/span>\u00a0<\/span><\/p>

The partnership expanded from English-only evaluation to five language variants and from evaluation-only to include response collection,\u00a0demonstrating\u00a0our ability to scale scope and complexity.<\/span><\/p>

Launching a new LLM or evaluating model performance across markets?\u00a0<\/span><\/span>\u00a0<\/span><\/h4>

Partner with\u00a0<\/span>DATAmundi<\/span>\u00a0for scalable, expert-level human evaluation across languages and response modes. Learn more about our\u00a0<\/span><\/span>AI Data Services<\/span><\/span><\/a>\u00a0or\u00a0<\/span><\/span>get in touch<\/span><\/span><\/a>\u00a0to discuss your project.<\/span><\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

How DATAmundi supported continuous LLM performance evaluation for a Fortune 100 AI research team through adaptive delivery, multilingual, multimodal evaluation, and structured human review. <\/p>\n","protected":false},"featured_media":59891,"template":"","meta":{"_acf_changed":false,"content-type":""},"case-study":[],"class_list":["post-59880","case-study","type-case-study","status-publish","has-post-thumbnail","hentry"],"acf":[],"yoast_head":"\nDATAmundi<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"\/\" \/>\n<meta property=\"og:locale\" content=\"pl_PL\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:site_name\" content=\"DATAmundi\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"CollectionPage\",\"@id\":null,\"url\":\"\",\"name\":\"\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/dmi5324.dotlogicstest.com\\\/pl\\\/#website\"},\"breadcrumb\":{\"@id\":\"#breadcrumb\"},\"inLanguage\":\"pl-PL\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"#breadcrumb\",\"itemListElement\":[]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/dmi5324.dotlogicstest.com\\\/pl\\\/#website\",\"url\":\"https:\\\/\\\/dmi5324.dotlogicstest.com\\\/pl\\\/\",\"name\":\"DATAmundi\",\"description\":\"Our Data. 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