Using LangExtract and Gemma 3 for structured information extraction from unstructured text in insurance polices
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Updated
Aug 29, 2025 - Python
Using LangExtract and Gemma 3 for structured information extraction from unstructured text in insurance polices
⚡ AI-powered content intelligence with structured data extraction. Self-improving prompts, customizable templates, and feedback learning. Supports PDFs, multiple AI providers.
LangExtract AWS Bedrock support
Verifiable Document Extraction & Auditing Tool using Google LangExtract + Gemini 2.5.
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My experiment with langextract - a Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
text analysis with langextract
The RAG Structured Data System is an advanced solution using langextract, designed specifically for conversational interfaces over structured datasets. Unlike traditional RAG systems that work with unstructured text, this system excels at handling tabular data from Excel, CSV, and JSON datasets while preserving granularity and precision
Experimenting langextract for possible use case
Contains all my python things...
A powerful, configurable text extraction system for building knowledge graphs
Ask questions about any YouTube video to this LLM powered transcriber.
🚀 Automatización inteligente que transforma mensajes caóticos de clientes en acciones estructuradas. Utiliza Python (Flask), Google LangExtract y n8n para diseccionar textos con múltiples intenciones, categorizarlos mediante IA y enrutarlos automáticamente a departamentos específicos (Ventas, Soporte, Administración). Ideal para eliminar cuellos d
High-performance Hybrid RAG pipeline using LlamaIndex, MinerU, GLiNER, and LangExtract. Features advanced metadata enrichment, BM25-Vector fusion, and LaTeX-enabled synthesis for complex document analysis.
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