In this post, we present a straightforward yet revealing task: classifying 25 philosophical and scientific arguments as either deductive or inductive. We tested Mistral Le Chat on this argument classification task to evaluate its ability to distinguish between these fundamental forms of reasoning. Le Chat demonstrated a solid grasp of
In two recent blog posts, we demonstrated how scanned PDFs can be processed using Mistral’s tools—first via a prompt-based approach in Mistral Le Chat, and then through the Mistral OCR API. Both methods effectively extracted readable, structured text from complex documents. But how well do other generative AI
When working with scanned documents, having direct access to a reliable OCR API can make text extraction faster, more consistent, and easier to integrate into existing workflows. In a previous post, we explored a prompt-based solution using Mistral’s Le Chat interface—which produced clean results but missed certain elements
Mistral’s GenAI capabilities make extracting text from scanned documents remarkably easy without relying on traditional OCR software. In this post, we demonstrate how scanned PDFs can be processed directly through a prompt-based interaction using Mistral Le Chat—producing clean, editable .txt outputs with minimal effort. Input file We tested
If your goal is to generate a downloadable .txt file—be it for survey responses, formatted data, or any structured text—not all models can deliver. In this case study, we tested various models to see whether they can create actual .txt files rather than just displaying text or offering
Interview metadata often arrives in semi-structured formats, making it difficult to analyse or integrate into standard research workflows. This short prompt-based approach shows how GenAI can transform a JSON file containing interview-related metadata into a clean, structured Excel (.xlsx) file—in seconds, without requiring any programming knowledge. The method enables
Classifying gender based on names might initially appear straightforward, yet different AI models vary significantly in how accurately and effectively they handle this task. This blog explores the performance of various models when provided with a structured prompt for name-based gender classification using an uploaded .xlsx file. The evaluation specifically
