Hey Product Hunt! 👋 I'm Shuaib, founder of SchemaMind. Here's the problem I kept hitting: every data team I talked to was spending 60–80% of their time just preparing data — manually mapping columns, writing brittle ETL pipelines, and wrangling PDFs into spreadsheets. The actual analysis? An afterthought. So I built SchemaMind — the Generative Data Intelligence platform. Here's how it works: Point it at your sources (SQL DB, CSV, Excel, PDF — all at once) Ask your question in plain English: "Show 30-day readmission rates by diagnosis and age group" SchemaMind automatically extracts metadata, maps semantically similar columns (even if they're named "client_id" vs "customer_id" vs "pt_id"), generates and self-heals the retrieval commands, and returns one clean, unified dataset What makes it different from every ETL tool out there: No schema knowledge required — it reads and understands your structure automatically Semantic column fusion — uses embeddings to match fields across sources even when naming differs Self-healing queries — if a command fails, it corrects itself using a secondary LLM PDF/DOCX native — tables in reports and invoices are first-class data sources Column lineage — every field in your unified output traces back to its origin The patent (Application No - PCT/IB2026/051254) covers the core AI-driven extraction and fusion architecture. We're live at 👉 www.schemamind.tech Would love your feedback — especially from data engineers and analysts who feel this pain daily. What's the messiest data fusion problem you've had to solve manually? Drop it below and I'll show you how SchemaMind handles it. 🚀

SchemaMind

The GPT for enterprise data - unified datasets, instantly

The GPT for enterprise data - unified datasets, instantly