{"id":5509,"date":"2026-03-02T14:31:32","date_gmt":"2026-03-02T14:31:32","guid":{"rendered":"https:\/\/hamilton.global\/?p=5509"},"modified":"2026-03-03T08:36:51","modified_gmt":"2026-03-03T08:36:51","slug":"synthetic_data-in-research","status":"publish","type":"post","link":"https:\/\/hamilton.global\/en\/synthetic_data-in-research\/","title":{"rendered":"Synthetic Data and AI-Augmented Research"},"content":{"rendered":"<h2><strong>Synthetic data, anchored in human evidence.<\/strong><\/h2>\n<p>We accelerate research with AI to generate synthetic datasets that reproduce real market patterns, with a clear objective: to reach actionable conclusions faster and reserve human fieldwork for what really requires it.<\/p>\n<h2><strong>What are they?<\/strong><\/h2>\n<p>Synthetic data is information generated by AI models that replicates the statistical structure and relationships observed in real research data (human sample), without copying individual records.<\/p>\n<h2><strong>How we do it <\/strong><\/h2>\n<p>Our approach combines two pillars:<\/p>\n<ul>\n<li><strong>Probabilistic models<\/strong> (random sampling and dependency modeling) to preserve key relationships.<\/li>\n<li><strong>Deep learning models<\/strong> (unsupervised approach combining GAN\/VAE type architectures) to generate robust synthetic datasets.<\/li>\n<\/ul>\n<blockquote>\n<p style=\"text-align: center;\"><em><strong>We do not develop databases &quot;from scratch&quot;. Our approach requires a real, human-generated dataset as a starting point.<\/strong><\/em><\/p>\n<\/blockquote>\n<h2><strong>How to configure <\/strong><\/h2>\n<blockquote>\n<p style=\"text-align: center;\"><strong><em>WHAT YOU NEED IN JUST THE RIGHT AMOUNT<\/em><\/strong><\/p>\n<\/blockquote>\n<p>Each project is defined in three steps:<\/p>\n<ol>\n<li><strong>Training base \/ reference<\/strong>: historical studies or high-quality datasets available.<\/li>\n<li><strong>Defining the business challenge<\/strong>: what decision will be made (and what variables should support it).<\/li>\n<li><strong>Control rules (guardrails)<\/strong>: what relationships should be preserved (segments, use, attitudes\u2026) and what is excluded to avoid noise or sensitivity.<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n<h2><strong>Quality and credibility: <\/strong><\/h2>\n<p>To ensure that the result is <strong>reliable and usable<\/strong>Each model includes a validation package with:<\/p>\n<ul>\n<li><strong>Distributions and univariate behavior<\/strong> (behavior of each variable).<\/li>\n<li><strong>Distributions and bivariate analysis<\/strong> (conditional relationships between variables).<\/li>\n<li><strong>Multivariate Distributions and Analysis <\/strong>(Homegeneities, ADM, comparative PCA, Clustering stability (ARI), RMSE, Adversarial test)<\/li>\n<li><strong>Correlations<\/strong> (matrix relationship structure).<\/li>\n<li><strong>Distances<\/strong> (synthetic proximity vs. original with Maximum Mean Discrepancy (MMD) and Jensen-Shannon distance).<\/li>\n<\/ul>\n<p><img decoding=\"async\" class=\"wp-image-5517 aligncenter\" src=\"https:\/\/hamilton.global\/wp-content\/uploads\/2026\/03\/Accuracy-Data.png\" alt=\"accuracy data\" width=\"615\" height=\"334\" srcset=\"https:\/\/hamilton.global\/wp-content\/uploads\/2026\/03\/Accuracy-Data.png 615w, https:\/\/hamilton.global\/wp-content\/uploads\/2026\/03\/Accuracy-Data-480x261.png 480w\" sizes=\"(min-width: 0px) and (max-width: 480px) 480px, (min-width: 481px) 615px, 100vw\" \/><\/p>\n<p>The accuracy of synthetic data is not evaluated by a simple comparison of means. It is analyzed at three key levels: the preservation of relational structure, the stability of segments, and predictive robustness in cross-validations. When a model trained on synthetic data is able to reliably predict real-world data, we can speak of operational equivalence.<\/p>\n<h2><strong>Where <em>YEAH<\/em> adds value <\/strong><\/h2>\n<ul>\n<li><strong>Innovation and concept\/claim screening<\/strong>: prioritize ideas before full human validation.<\/li>\n<li><strong>Coverage of difficult targets \/ small samples<\/strong>: \u201cfilling gaps\u201d when the human sample is unavailable or expensive.<\/li>\n<li><strong>Speed and agility<\/strong>: generate scenarios and preliminary readings in less time.<\/li>\n<li><strong>Simulation<\/strong>: explore rare or infrequent situations that are difficult to capture in reality.<\/li>\n<\/ul>\n<h2><strong>When <em>NO<\/em> We recommend it<\/strong><\/h2>\n<ul>\n<li>When you need insight <strong>cool<\/strong> and firsthand (crisis, abrupt market changes).<\/li>\n<li>When there is no <strong>baseline<\/strong> solid for training\/anchoring the model.<\/li>\n<li>When the decision requires human evidence for reasons <strong>regulatory\/legal<\/strong>.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<blockquote>\n<p style=\"text-align: center;\">In these cases it can be used as <strong>pre-analysis<\/strong>but not as a substitute for human fieldwork.<\/p>\n<\/blockquote>\n<p>&nbsp;<\/p>\n<p style=\"text-align: center;\"><a href='https:\/\/hamilton.global\/en\/contactanos\/' class='small-button smallblue' target=\"_blank\">REQUEST MORE INFORMATION<\/a><\/p>\n<span class=\"et_bloom_bottom_trigger\"><\/span>","protected":false},"excerpt":{"rendered":"<p>Datos sint\u00e9ticos, anclados en evidencia humana. Aceleramos la investigaci\u00f3n con IA para generar datasets sint\u00e9ticos que reproducen los patrones reales del mercado, con un objetivo claro: llegar antes a conclusiones accionables y reservar el fieldwork humano para lo que realmente lo requiere. Qu\u00e9 son Los datos sint\u00e9ticos son informaci\u00f3n generada mediante modelos de IA que [&hellip;]<\/p>","protected":false},"author":4,"featured_media":5515,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"off","_et_pb_old_content":"","_et_gb_content_width":""},"categories":[204,201],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Datos Sint\u00e9ticos y Research Aumentado con IA<\/title>\n<meta name=\"description\" content=\"La investigaci\u00f3n con IA para generar datasets sint\u00e9ticos que reproducen los patrones reales del mercado, con un objetivo claro: llegar antes a conclusiones accionables y reservar el fieldwork humano para lo que realmente lo requiere.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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