Alternatives
Products that do what NeuralShield does
Private AI research engine that never leaves your machine
- 1SA
Alright so if you run a self-hosted blog, you've probably noticed AI companies scraping it for training data. And not just a little (RIP to your server bill). There isn't much you can do about it without cloudflare. These companies ignore robots.txt, and you're competing with teams with more resources than you. It's you vs the MJs of programming, you're not going to win. But there is a solution. Now I'm not going to say it's a great solution...but a solution is a solution. If your website contains content that will trigger their scraper's safeguards, it will get dropped from their data…
Dec 2025 · github.com
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- 8WP
Anthropic and OpenAI's publicly available models are explicitly guard-railed so that they refuse offensive tasks. And their cyber-focussed models are gated for enterprises. This leaves SMEs and mid market open to major vulnerabilities. AI can be used as both an adversarial and defensive tool in the world of cyber. A worst case outcome is if only the adversaries have access. Meanwhile, most existing AI cyber tools are just wrappers. The problem is that they still have all the guardrails on from the foundation model where they will inherit its refusals. For this project we've post-trained a…
Jun 2026 · argusred.com
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- 14AE
Anchor Engine is ground truth for personal and business AI. A lightweight, local-first memory layer that lets LLMs retrieve answers from your actual data—not hallucinations. Every response is traceable, every policy enforced. Runs in <3GB RAM. No cloud, no drift, no guessing. Your AI's anchor to reality. We built Anchor Engine because LLMs have no persistent memory. Every conversation is a fresh start—yesterday's discussion, last week's project notes, even context from another tab—all gone. Context windows help, but they're ephemeral and expensive. The STAR algorithm (Semantic Traversal And…
Mar 2026 · github.com
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Immutable deterministic security architecture for AI systems
Apr 2026 · sovereign-shield.net
- 16MA
Hey HN, We’ve been heads-down building MOSS - a semantic memory layer that brings AI-powered search and personalization fully on-device (No cloud | No latency | No data leaving the user’s device) We just launched a live demo showing MOSS running entirely in-browser, performing lightning-fast semantic search over local in-browser VectorDB. This unlocks a new class of privacy-first, hybrid AI experiences that work even without a server connection. If you’re curious about: - how to run AI search right inside the browser - the technical challenges behind on-device vector search - why we believe…
2025 · twitter.com
- 17MC
Hey Hacker News Community! Mindgard.ai (https://mindgard.ai/) is a way to assess, detect, and respond to cyber-attacks and data leakage against all forms of AI/ML, including LLMs, GenAI and any other AI assets including 3rd party supply chain. It also helps you to discover and learn more about the threats out there for AI. Our current platform version allows you to test different models and variations of attacks. We are Peter and Steve, the founders behind the Mindgard AI Security Labs at mindgard.ai. Our journey began with a simple yet challenging goal: to tackle the…
2024
- 18RG
Hey HN, I wanted to share something I’ve been working on: *RAG-Guard*, a document AI that’s all about privacy. It’s an experiment in combining Retrieval-Augmented Generation (RAG) with AI-powered question answering, but with a twist — your data stays yours. Here’s the idea: you can upload contracts, research papers, personal notes, or any other documents, and RAG-Guard processes everything locally in your browser. Nothing leaves your device unless you explicitly approve it. ### How It Works - * Zero-Trust by Design*: Every step happens in your browser until you say otherwise. - * Local…
2025 · github.com
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Hi HN, I'm one of the creators of HoundDog.ai (https://github.com/hounddogai/hounddog). We currently handle privacy scanning for Replit's 45M+ creators. We built HoundDog because privacy compliance is usually a choice between manual spreadsheets or reactive runtime scanning. While runtime tools are useful for monitoring, they only catch leaks after the code is live and the data has already moved. They can also miss code paths that aren't actively triggered in production. HoundDog traces sensitive data in code during development and helps catch risky flows (e.g., PII…
Feb 2026 · github.com
- 20WB
Hey HN! Alex and Zack from Nexa AI here. We are excited to share a project our team has been passionately working on recently, in collaboration with Jiajun from Meta, Qun from San Francisco State University, and Xin and Qi from the University of North Texas. Running AI models on edge devices is becoming increasingly important. It's cost-effective, ensures privacy, offers low-latency responses, and allows for customization. Plus, it's always available, even offline. What's really exciting is that smaller-scale models are now approaching the performance of large-scale closed-source models for…
2024 · github.com
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Built StopX after struggling with the limitations of traditional blocklist-based filters. Most existing solutions rely on static URL databases that are constantly outdated and easily bypassed. Our approach uses proprietary WebShield™ technology that combines: Real-time AI image recognition for visual content analysis Contextual URL pattern matching beyond simple domain blocking Cross-device synchronization with encrypted settings sync Military-grade bypass protection with stealth mode operation The interesting technical challenge was achieving 99.7% accuracy while maintaining sub-100ms…
2025 · stopx.today
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Local, gradient-free neuro-symbolic memory engine combining Hyperdimensional Computing (HDC/VSA), Hebbian plasticity, and graph triples for offline AI. - roandejager/Hillock
7d ago · github.com
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