Juan is the co-founder and CEO of anyformat. He is a nuclear engineer and holds a PhD in experimental Physics from Sorbonne University (Paris 6). He spent years building production AI systems at Clarity AI and was the founding GenAI engineer at Latency. He writes about document intelligence, agentic extraction architectures, confidence calibration, and the gap between document AI demos and production. anyformat is backed by Kibo Ventures, 4Founders Capital, and Abac Nest Ventures, and serves customers including L'Oréal, IAG, Iberia, and the Government of Singapore.
Articles
Long Documents Are the Production Case: Why 300-Page PDFs Break Extraction Systems and How We Solved It
· Most extraction tools demo on 5-page invoices. Production runs on 300-page filings. We explain why long documents break LLMs and chunking pipelines, how the rest of the field is approaching the problem, and the parse-extract architecture anyformat ships so document teams stop firefighting PDFs.If You Can't Point to It, You Can't Trust It: Why Visual Grounding Is the Foundation of Auditable Document AI
· Most document AI systems can't show where extracted values came from. Learn why visual grounding — linking every output to its exact source region — is the key to auditable, trustworthy document automation.Beyond Accuracy: The Document AI Metrics That Actually Predict Production Success
· Accuracy benchmarks hide silent failures in document processing. Learn the 5 metrics — including confidence calibration, straight-through processing rate, and silent failure rate — that separate production-grade IDP systems from demo-ware.The Paper Paradox: Why Document AI Still Hasn't Replaced Manual Work
· 61% of document processing workflows still involve paper. 66% of new projects replace failed ones. The problem isn't the AI. It's trust.The End of 'We'll Build It In-House': 5 Document Processing Predictions for 2026
· Why this is the year enterprises stop reinventing the wheel on document infrastructure. Buy vs. build finally tips—for non-core problems.Making AI Data Extractions Trustworthy
· This piece introduces a method for scoring the confidence of AI-generated structured outputs, like JSONCómo desbloquear el valor de los datos no estructurados
· Las empresas acumulan datos sin usar. La IA Generativa convierte ese caos en innovación, eficiencia y ventaja competitiva.Una Nueva Era: Los Nobel de Hopfield, Hinton y Hassabis y el Futuro de la Inteligencia Híbrida
· Los Nobel de Física y Química 2024 reconocen el impacto histórico de la IA en la ciencia y la industria, inaugurando una era de colaboración humano-máquina.