Search Results for "privacy"
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Showing 200 open source projects for "privacy"
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OpenAI Privacy Filter
Bidirectional token-classification model for identifiable info
OpenAI Privacy Filter is an open-weight machine learning model designed to detect and mask personally identifiable information in text with high efficiency and contextual awareness. It operates as a bidirectional token classification system that labels sensitive data in a single forward pass rather than generating text sequentially, enabling fast processing for large datasets. -
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Obscura
The headless browser for AI agents and web scraping
Obscura is a security-focused project aimed at providing tools and techniques for enhancing privacy, anonymity, and operational security in digital environments. It is designed for users who need to obscure their digital footprint and reduce traceability across systems. The project typically includes utilities for masking identity, managing secure communication, and mitigating surveillance risks. It emphasizes practical implementations of privacy-preserving workflows rather than purely theoretical approaches. ... -
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Odysseus
Self-hosted AI workspace from PewDiePie
...It provides an interface for chat, agents, tools, research, model serving, email, and other AI-assisted productivity tasks. The project emphasizes local-first and privacy-first operation, with no telemetry by default. It is built for users who want a personal AI environment rather than a fully hosted commercial assistant. Odysseus can work with local models while still leaving room for external API use when the user chooses. It is especially useful for developers, researchers, and privacy-conscious users who want to consolidate AI work into one self-managed workspace. -
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Ollama
Run models like Kimi-K2.5, GLM-5, DeepSeek, gpt-oss, Gemma, Qwen etc.
...Ollama also integrates with popular developer tools and AI agents, allowing seamless workflows across coding environments and applications. It supports REST APIs, Python, and JavaScript SDKs, making it easy to build AI-powered features into software projects. Overall, Ollama focuses on privacy, local-first AI execution, and developer-friendly tooling for building with open models. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Opacus
Training PyTorch models with differential privacy
...Open source, modular API for differential privacy research. Everyone is welcome to contribute. ML practitioners will find this to be a gentle introduction to training a model with differential privacy as it requires minimal code changes. Differential Privacy researchers will find this easy to experiment and tinker with, allowing them to focus on what matters. -
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Appfl
Advanced Privacy-Preserving Federated Learning framework
APPFL (Advanced Privacy-Preserving Federated Learning) is a Python framework enabling researchers to easily build and benchmark privacy-aware federated learning solutions. It supports flexible algorithm development, differential privacy, secure communications, and runs efficiently on HPC and multi-GPU setups. -
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Meetily
Privacy first, AI meeting assistant with 4x faster Parakeet/Whisper
This project is a privacy-first AI meeting assistant that captures meeting audio, produces real-time transcripts, and generates summaries while keeping processing entirely on your own machine or infrastructure. It’s built for organizations that want meeting intelligence without sending recordings or transcripts to third-party cloud services, which helps address compliance and data sovereignty requirements. -
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Perplexica
Perplexica is an AI-powered answering engine.
...It also enhances the experience with widgets and rich search types like images, videos, and domain-limited queries. With local search history, file uploads, and an easy Docker-based setup, it’s built for everyday research without sacrificing control or privacy. -
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Voicebox
The open-source voice synthesis studio powered by Qwen3-TTS
Voicebox is a local-first voice synthesis studio that aims to bring professional, DAW-like voice generation workflows to a desktop app while keeping models and voice data entirely on your machine. It positions itself as an open-source alternative to cloud voice platforms by emphasizing privacy, offline use, and freedom from subscriptions or usage caps. The tool supports downloading voice models, cloning voices from short audio samples, and generating speech locally, then organizing the results using studio-oriented editing concepts. A standout capability is its multi-track timeline editor and supporting audio tools (like trimming and conversation mixing), which let creators compose multi-voice scenes instead of generating single clips in isolation. ... -
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Pfl Research
Simulation framework for accelerating research
A fast, modular Python framework released by Apple for privacy-preserving federated learning (PFL) simulation. Integrates with TensorFlow, PyTorch, and classical ML, and offers high-speed distributed simulation (7–72× faster than alternatives). -
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Activepieces
Open Source AI Automation
...It supports integrations with popular services like Slack, Google Sheets, and Discord, and allows users to create custom pieces to suit unique needs. With real-time logs, version history, and scheduling, Activepieces is positioned as a compelling alternative to Zapier for open-source and privacy-conscious users. -
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Claude Code
Claude Code is an agentic coding tool that lives in your terminal
...The tool is designed to simplify development by automating repetitive work and providing instant clarifications on code behavior. User feedback and usage data are collected responsibly, with strict privacy safeguards and limited retention, ensuring no feedback is used to train generative models. Claude Code is open and actively maintained with community-driven bug reporting and feature requests. Its natural language interface makes advanced coding workflows accessible without leaving your coding environment. -
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Steel Browser
Open Source Browser API for AI Agents & Apps
Steel Browser is a privacy-focused web browser built with security and performance optimizations, designed to minimize tracking and enhance user control. -
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Handy STT
A free, open source, and extensible speech-to-text application
Handy is a free, open-source, offline speech-to-text application built for privacy, accessibility, and extensibility. Developed using Tauri (Rust + React/TypeScript), it runs natively across Windows, macOS, and Linux while performing local speech recognition without sending any audio to cloud servers. Handy allows users to start transcription instantly using a configurable keyboard shortcut—press to record, release to transcribe—and automatically pastes the resulting text into any active text field. ... -
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AgenticSeek
Fully Local Manus AI. No APIs, No $200 monthly bills
...It also supports hands-free workflows such as automated web form interaction and information extraction. Overall, the project functions as a self-hosted, multi-capability AI agent designed for users who prioritize autonomy, privacy, and local execution. -
16
COCOON
Confidential Compute Open Network, Decentralized AI Inference on TON
COCOON is a privacy-aware desktop client framework designed by the developers of Telegram to provide a modern, secure, and extensible environment for building messaging and communication applications. At its core, it combines native desktop performance with web-like flexibility, packing a renderer, UI components, and plugin architecture that allows developers to craft rich experiences similar to those found in native apps. -
17
MimiClaw
Run OpenClaw on a $5 chip
...Even though it’s running on minimal hardware, MimiClaw maintains local memory that persists across power cycles, enabling context continuity over time without relying on cloud services. Its architecture emphasizes privacy, low power, and portability, ideal for personal or hobbyist use cases where privacy and local control matter. -
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Synthetic Data Generator
SDG is a specialized framework
Synthetic Data Generator is an open-source framework designed to generate high-quality synthetic tabular datasets that replicate the statistical characteristics of real data while avoiding privacy risks. The platform enables developers and data scientists to create artificial datasets that preserve important relationships between variables without containing sensitive personal information. This makes the generated data suitable for tasks such as machine learning model training, testing software systems, sharing datasets across organizations, and conducting research without violating privacy regulations. ... -
19
nesa
Run AI models end-to-end encrypted
nesa is an open-source initiative focused on building decentralized AI infrastructure that enables secure, verifiable, and privacy-preserving machine learning and inference across distributed environments. The project aims to address key challenges in modern AI systems, such as data privacy, trust, and centralization, by leveraging cryptographic techniques and decentralized architectures. NESA allows developers to run AI computations in a way that ensures data integrity and confidentiality, making it particularly relevant for applications involving sensitive or regulated data. ... -
20
Frigate NVR
NVR with realtime local object detection for IP cameras
...It also provides event recording, snapshot management, and searchable video history to improve home or small-business security workflows. Overall, Frigate functions as a privacy-focused, AI-powered NVR platform for intelligent video monitoring. -
21
Hyprnote
Local-first AI Notepad for Private Meetings
Hyprnote is an open-source, privacy-first AI notepad app designed for taking notes during meetings—transcribing audio (microphone and system) and generating context-rich summaries using on-device AI models like Whisper and HyprLLM, all without any data leaving your machine.(turn0search7, turn0search1). Listens to your meetings while you write. Crafts smart summaries based on your quick notes. -
22
BrowserOS
Agentic browser; privacy-first alternative to ChatGPT Atlas
...Rather than just doing standard browsing, it places AI intelligence at the core: you can connect your own API keys (for e.g., OpenAI, Anthropic, Google Gemini) or run local models (via e.g., Ollama) so that your browsing data and automation stay on your machine — privacy and control are emphasized throughout. The interface remains familiar to users of Chrome (including support for Chrome extensions), but adds new capabilities: the browser can automate tasks for you, help you research by extracting and summarizing content, and enable agent-based workflows (e.g., “go fetch this info,” “fill this form,” “monitor this site”). ... -
23
NVIDIA FLARE
NVIDIA Federated Learning Application Runtime Environment
NVIDIA Federated Learning Application Runtime Environment NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflows(PyTorch, TensorFlow, Scikit-learn, XGBoost etc.) to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration. NVIDIA FLARE is built on a componentized architecture that allows you to take federated learning workloads from research and simulation to real-world production deployment. -
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LLM.swift
LLM.swift is a simple and readable library
LLM.swift is a Swift package that enables developers to run Large Language Models (LLMs) directly on Apple devices, including iOS, macOS, and watchOS. By leveraging Apple's hardware and software optimizations, LLM.swift facilitates on-device natural language processing tasks, ensuring user privacy and reducing latency associated with cloud-based solutions. -
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Open CoDesign
Open-source Claude Design alternative
...The system supports multiple model providers and integrates directly with existing developer tools, enabling seamless workflows without vendor lock-in. It generates HTML, React components, PDFs, and other outputs in real time, rendered in a sandboxed preview environment. The architecture emphasizes privacy, with all data stored locally and no mandatory accounts or telemetry. It also includes built-in design skill modules and allows users to define custom styles and preferences. Overall, it bridges AI generation and design engineering into a unified, programmable workflow.