The open source PII and PHI redaction and de-identification engine
An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.
An automated document analyzer for Paperless-ngx using OpenAI API, Ollama, Deepseek-r1, Azure and all OpenAI API compatible Services to automatically analyze and tag your documents.
Scalable engine for detecting and redacting PHI/PII from healthcare documents and data streams. Supports OCR and NLP-based extraction, configurable redaction rules, audit logging, and containerized deployment to help teams meet HIPAA and data-privacy requirements.
Discover the mesmerizing dance of the Golden Ratio in Flutter's animated visualization.
PII Anonymizer service based on python with FastAPI
module system for question classification and answer enhancement using the Phi model, with Arabic & English support and an interactive Streamlit UI.
Square root of the golden ratio.
Philter Java SDK
Java Client SDK for Airlock
A hands-on collection of practical notebooks for learning and building with LLMs , including prompt engineering, RAG, fine-tuning, and evaluation. Built for aspiring AI engineers using only free and open-source tools.
Philter redacts sensitive information such as PII and PHI in text.
A modular multi-agent AI system that classifies and routes documents (Email, JSON, PDF) using LLMs, with shared memory and format-intent detection. Built with Python and Ollama. This project was developed as part of an internship task focused on building a practical multi-agent AI document processing pipeline using LLMs and shared memory.
Golden ratio.
Higher performance OpenAI LLM service than vLLM serve: A pure C++ high-performance OpenAI LLM service implemented with GPRS+TensorRT-LLM+Tokenizers.cpp, supporting chat and function call, AI agents, distributed multi-GPU inference, multimodal capabilities, and a Gradio chat interface.
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