Alternatives
Products that do what EPH4 does
Ephemeral RAG Pipeline Built for Compliance and Data Privacy
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A lightweight engine for durable execution / deterministic workflows I built with Rust, wasmtime and the WASM Component Model. Its main use is running reliable, long-running workflows that can automatically resume after failures. Looking for feedback on the approach and potential use cases!
2025 · obeli.sk
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2021 · github.com
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2021 · ephemere.app
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This project is a tool for engineers who live in the terminal and are tired of losing their command history to ephemeral servers or fragmented `.bash_history` files. If you’re jumping between dozens of boxes, many of which might be destroyed an hour later, your "local memory" (the history file) is essentially useless. This tool builds a centralized, permanent brain for your shell activity, ensuring that a complex one-liner you crafted months ago remains accessible even if the server it ran on is long gone. The core mechanism wants to be a "zero-touch" capture that happens at the connection…
Jan 2026 · github.com
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2017 · engblog.nextdoor.com
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2014 · ephchat.com
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I’ve been experimenting with structured logic as a way to frame search spaces — not in an academic way, just as a personal project. I wanted to know: what happens if you initialize a brute-force run with a simple equality like xy = x / y? Not as a filter, just as a logical ignition point. I used AES-256-CBC encrypted files with UUID passwords and tested against a 1 million UUID space. It cracked it in under 40 seconds. Then I scaled it to a 1 billion UUID range, and it still found the key without issue. This isn’t a crypto tool, and I’m not trying to solve any cryptographic problems.…
2025 · github.com
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Hey everyone! This is XTrace. Wanted to share what we’ve been working on for the past year. We built a private vector database from the ground up that performs similarity search on encrypted vectors. The server never sees your plaintext embeddings or documents. The problem we’re trying to solve: every vector DB today requires plaintext on the server. If you're doing RAG over sensitive data (medical, legal, financial), your embeddings — which researchers have shown can be inverted to recover original text — sit exposed on someone else's infrastructure. XTrace encrypts everything on your…
Apr 2026 · github.com
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I built this after seeing multiple teams accidentally ship API keys in their frontend code. The problem: Modern web development moves fast. You're vibe-coding, shipping features, and suddenly your AWS keys are sitting in a tag visible to anyone who opens DevTools. I've personally witnessed this happen to at least 3-4 production apps in the past year alone. KeyLeak Detector runs through your site (headless browser + network interception) and checks for 50+ types of leaked secrets: AWS/Google keys, Stripe tokens, database connection strings, LLM API keys (OpenAI, Claude, etc.), JWT…
Nov 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
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Byte-Vision is a privacy-first document intelligence platform that transforms static documents into an interactive, searchable knowledge base. Built on Elasticsearch with RAG (Retrieval-Augmented Generation) capabilities, it offers document parsing, OCR processing, and conversational AI interfaces.
2025 · github.com
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- Discovering the most effective RAG pipeline for your specific data and use case can be daunting. It requires experimenting with various RAG modules and configurations, which are both time-consuming and complex. - AutoRAG addresses this challenge by automatically evaluating different combinations of RAG modules and their parameters. You don't need to write implementation code yourself; everything is set up through a single YAML file. - Our aim is to save you the hassle of continuously adapting to new RAG modules and configurations. Instead, you can focus on developing robust data for your…
2024 · github.com
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2024 · securelog.com
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Today you can easily adopt AI coding tools because you have git for branching and rolling back if AI writes bad code. We haven't seen this same capability for data and decided to build it ourselves. Nile is a new kind of data lake, purpose built for using with AI. It can act as your data engineer or data analyst creating new tables and rolling back bad changes in seconds. We support real versions for data, schema, and ETL. We'd love your feedback on any part of what we are building - https://getnile.ai/ What do you think?
Jan 2026
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Needed this in my own work, anonymizing PII/PHI and decided to build this because presidio didn't really cut it for our use-case. Try it and maybe let me know if you have any feedback :)
2025 · github.com
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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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