Technical resources
We write about what we audit, not about what's trending.
Field notes, not generic marketing content — on AI governance, algorithm auditing, and two decades of applied rigor.
BIT Library — four books to read cover to cover. Data Analysis, Deep Learning, Big Data & Data Engineering, and MLOps: theory, code, and reproducible labs (in Spanish). Open the library → Applied technology. Data. Intelligence. BIT's technical blog, with the same rigor applied to statistics, machine learning, deep learning, big data, MLOps, and IoT (in Spanish). Visit the blog →
What it means to audit an AI system under ISO/IEC 42001 (and why it should matter to your company)
The first international standard for AI governance, explained in concrete terms: what it reviews, why it matters now, and how it connects to traditional auditing.
→Five questions every risk manager should ask their AI vendor
An actionable checklist for evaluating AI vendors with the same rigor already applied to fintech vendors.
→From auditing data to auditing algorithms: a decade of lessons in applying technical rigor
Three lessons from more than a decade auditing critical information systems, applied today to AI governance.
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