This repository contains an end‑to‑end pipeline for training, deploying and consuming a LLM‑based invoice extractor.

This repository hosts the source code for an Invoice Extractor application powered by a Language Model (LLM). The application leverages advanced natural language processing techniques to intelligently extract relevant information from invoices.

This repository contains files of a Multi-Language Invoice Extractor project utilizing the Google Gemini Pro LLM Model, enabling accurate extraction and processing of invoice data in various languages, significantly streamlining the accounts payable process for a diverse client base.

AI-powered Invoice Data Extraction Tool – Upload any document (PDF/image) and extract key information in structured JSON format using OCR and vision-based LLM techniques, including robust stamp detection.

This system is a fully automated AI-driven pipeline designed to extract, validate, and synchronize invoice data with enterprise systems in real time. It combines OCR, LLM-based field extraction, rule-based validations, and multi-channel ingestion (Email + Local Folder Watcher) to deliver a production-grade, autonomous workflow.

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Extract information from receipts and invoices in a structured way using LLM-based approach.

A Local LLM based invoice extractor which extract every information required form an bill of the indian standard billing system structure

Automated Invoice Extractor is a Flask-based API that leverages OCR (EasyOCR) and LLMs (Ollama) to automatically extract, validate, and structure invoice data into clean JSON. It supports invoice image/PDF processing, JSON repair, and rule-based invoice detection for seamless automation.

Autonomous pipeline for extracting structured data from unstructured invoices and contracts using n8n and LLM-based parsing.

Django-based InvoiceExtractor that allows users to upload PDF invoices and extract key details from it using LLMs

Intelligent Invoice Extractor is a GenAI-powered application that extracts structured invoice data from PDF invoices. The system automatically processes text-based PDFs using an LLM-driven extraction pipeline and exports results as clean JSON or CSV. OCR support for scanned invoices is fully implemented for local execution

A Python-based OCR-powered invoice parser that extracts structured data into JSON format and enables intelligent querying using LLM model.

FastAPI-based application for extracting structured invoice data using OCR (OCR.space API) and optional LLM-based formatting (via Groq). Supports image and PDF files, outputs raw text or structured JSON with invoice fields.

Developed an Invoice Extractor application using Gemini and large language models (LLMs). Enabled image uploads, OCR-based extraction, and an NLP query system. Achieved 78% precision in answering invoice-related queries, ensuring efficient data storage and processing.

A **Streamlit-based web application** that utilizes **Google Gemini Vision LLM** to extract and analyze invoice details from uploaded images. This AI-powered tool supports **multiple languages**, allowing users to upload an invoice image and receive insights based on the extracted text and structure.

It is an advanced invoice parsing tool designed to automate and enhance data extraction from PDF invoices using Large Language Models (LLMs). This intelligent system allows users to upload single or multiple invoices and leverages prompt-based querying to extract specific fields

Building a Python-based automation pipeline that ingests invoice files, extracts key data points using an LLM (Large Language Model), validates the mathematical accuracy of the invoice, and routes the data to the correct output destination.

Built an automated workflow using LangGraph and LLMs that extracts text from invoice images, generates MySQL insert queries, and updates totals dynamically based on feedback. Includes human approval before execution for accurate, end-to-end invoice data automation.

An end-to-end OCR system designed to extract and structure information from financial documents such as invoices and reports using LLM-based OCR (Llama-OCR), custom rule-based parsing, and an interactive Streamlit UI.

Intelligent Compliance Validator automates document validation by extracting text via OCR and evaluating compliance using an LLM based on predefined business rules. It streamlines invoice, PO, and GRN verification into a single automated workflow.

AI-Based Form Filling System using FastAPI and Gemma 3 4B — Automatically extracts data from images (invoices, receipts, bills) and fills digital forms. Powered by Ollama for LLM-based data extraction and semantic mapping. Ideal for R&D and prototype purposes.

AI-powered system that extracts data from invoice PDFs using OCR and enables natural-language querying across documents with LLMs and vector search. Includes GSTIN detection, API-based tax verification, and contextual AI-driven insights.

Extracts data from PDF, JPG, PNG using OCR via PyTesseract. Supports NER with local LLMs (Mistral) or HuggingFace models (Donut-base-finetuned-invoices). Outputs images highlighting detected information with bounding boxes.

AI-based invoice extraction system that processes images/PDFs to extract structured data. Uses OCR for text extraction and LLM to convert it into JSON. Data is stored in Supabase, enabling analytics like vendor-wise spending and monthly trends.

A Streamlit-based agentic system for intelligent document processing. It automatically ingests PDF and image documents, performs OCR, classifies document types (Invoices, Medical Bills, Prescriptions), extracts key-value data using OpenAI's LLMs with structured Pydantic schemas alongside a comprehensive validation report.