Alternatives
Products that do what JarvisMindAI (Beta Version) does
Upload docs, ask questions, get AI answers from your files.
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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
- 7WB
Mintlify Pro costs 250 USD per month. We wanted something similar (AI assistant and nice UI), but fully customizable and cheap. So we built GibsonAI docs in 1 day for about 50 USD. How we did it: Used Lovable for UI components + rendering MDX beautifully (Markdown stored in GitHub). Built an AI Agent for docs using Agno + Memori → personalized Q&A and “smart educator.” Stored embeddings in LanceDB and metadata in our SQL DB. Bonus: We can share our reusable design templates and source code so you can deploy on Vercel (or anywhere) and skip Lovable costs. Would love feedback on what features…
Sep 2025 · gibsonai.com
- 8CS
If you have developer documentation and want to boost your community with AI this is for you! Just pull in the base url of the site add some customization and get a sharable link for your chat, link it anywhere you want. I saw this trend in some places like gcp with Gemini, or Langchain or Supabase ask ai, but they're all custom-implemented solutions, not everyone wants to advocate developer resources to create the rag, deploy it and maintain it, you just want devs to build with your stuff, the more they can do the better, the quicker the better, and if they get a smooth experience while…
2024 · explainit.mzslabs.com
- 9AS
Upload markdown docs, get a support chatbot that answers with citations. The entire backend is one JS file — storage, search, and conversation history are handled by the runtime. Stack: Next.js + OnCell + OpenRouter. Demo: https://youtu.be/rWIU43pOH5Y
Apr 2026 · github.com
- 10AO
I've built an airgapped Retrieval-Augmented Generation (RAG) system for question-answering on documents, running entirely offline with local inference. Using Llama 3, Mistral, and Gemini, this setup allows secure, private NLP on your own machine. Perfect for researchers, data scientists, and developers who need to process sensitive data without cloud dependencies. Built with Llama C++, LangChain, and Streamlit, it supports quantized models and provides a sleek UI for document processing. Check it out, contribute, or suggest new features!
2024 · github.com
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RAG Web UI is designed to be the most straightforward way to build your own knowledge-based Q&A system. While other RAG (Retrieval-Augmented Generation) projects might be complex, we focus on making it super easy to understand and use. Why It's The Most Beginner-Friendly: Simple Document Management - Just upload your documents (PDF, DOCX, Markdown, Text) - System handles all the complex processing automatically - No need to worry about document chunking or vectorization - Documents update automatically in the background Easy-to-Use Chat Interface - Ask questions in plain language - Get…
2025 · github.com
- 13HG
Hi everyone, I use AI to get answer as much as I used Google before. So I built this little app that you can quickly get an answer by: - Press hotkeys -> Type your question -> Get answer It has web browsing feature, real-time search, rich content view, code highlighting. It's BYOK, supported OpenAI and its compatible API. I started learning swift and this is just handy. Just ask, it give the code example and explanation. Will support Windows and Linux soon Feel free to leave your feedback
2023 · thegums.co
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Hey, OpenAI recently released "assistants" - These have RAG built into the API, which means that you can provide up to 10.000 files to the assistant without the overhead of dealing with vector databases, splitting files into chunks and more. They work surprisingly well, so I've built a free simple tool to embed them on websites. It has no dependencies and simply uses fetch to communicate to my backend which proxies openai. In the future I plan to add more widget embedding options (currently only chat is available). Let me know if you have any specific questions about either the tool or…
2024 · rispose.com
- 16AB
I built a browser app for recording calls and turning them into transcripts/summaries without inviting a meeting bot. The current version is BYOK: you provide an OpenAI API key, stored locally in your browser. Recordings/projects stay in browser storage; selected audio/transcript text is sent to OpenAI only when you run transcription/summary. I am testing whether the wedge is real: no bot in the meeting, no SaaS workspace for recordings, summaries/exports afterward. I would appreciate feedback on the trust boundary and whether BYOK is acceptable for a first version.…
May 2026 · wocal.app
- 17IB
I’ve spent the last 2.5 months building a product that runs LLM-powered code reviews on my pull requests — and I just launched it. The tool is built specifically for solo developers. You install it on your repo, trigger a scan by creating a pull request, and it leaves structured review comments using OpenAI under the hood. Funnily enough, I used the dev version of this app to review its own pull requests while building it. It helped me spot bugs, simplify structure, and keep quality high — all with minimal need for another human in the loop. Things I want to try out in the next months : -…
2025 · codii.dev
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Hi HN, I’m Linn, the creator of ToolKuai (https://toolkuai.com). Like many of you, I’ve always been wary of "free" online file converters. Most of them are black boxes: you upload your private documents or images to a remote server, and you have no idea where that data ends up or how it’s being used to train models. I wanted to build a suite of tools (Video/Image compressor, OCR, AI Background Remover) that runs entirely in the browser. No files ever leave your machine. The Tech Stack To make this performant enough to rival server-side processing, I leaned heavily into modern…
Jan 2026 · toolkuai.com
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I've built VT Chat, a privacy-first AI chat application that keeps all your conversations local while providing advanced research capabilities and access to 15+ AI models including Claude 4 Sonnet and Claude 4 Opus, O3, Gemini 2.5 Pro and DeepSeek R1. Live: https://vtchat.io.vn | Source: https://github.com/vinhnx/vtchat The core difference is true local-first architecture. All chats are stored in IndexedDB with zero server storage. Your API keys never leave your browser, and I can't see them even as the developer. You can switch between OpenAI, Anthropic, Google…
2025
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Hey HN! I've been working on a side project to create an audio transcription API based on the OpenAI whisper model. Sign up link: https://whisperapi.com I tried to make the API really easy to use and get setup with. Also, because the Whisper model is so good, turns out I can offer the service for about 75% cheaper than what seems like the industry average. I'm always looking to make improvements, so would appreciate any feedback anyone has!
2022 · whisperapi.com
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Hey HN, I’m Julia, my team and I are building Rag-in-a-Box (https://www.joinable.ai/rag-in-a-box), hosted RAG service that let’s builders of any skill level launch their own RAG app loaded with their own data in minutes. [ What can you do ] 1. Load your documents (PDFs, CSV, PPTs, Word Docs, etc) and make them searchable instantly. All your data stays private and encrypted. 2. Choose latest open source LLM (Llama 4, Deepseek, GPT-oss, etc) to interact with your docs 3. Access your hosted RAG via API - build your own custom front end or integrate with your existing product…
2025 · joinable.ai
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Demo starts at 50m into the video. This was a bit terrifying to record because 2am the previous night everything was totally broken after a major refactor (so that we could add external LLM support as well as local GPUs). But pressure can be a useful force :-D We start with a stack deployed on my laptop without a GPU, pointing to together.ai so we can run open source LLMs easily without having to have access to a GPU. We show simple inference through the ChatGPT-like web interface (with users, sessions etc) and then simple drag'n'drop RAG. Then we show some helix apps defined as yaml: Marvin…
2024 · youtube.com
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Hi HN, While building RAG agents, I noticed a lot of token budget was wasted on formatting overhead (HTML tags, JSON structure, whitespace). Existing solutions felt too heavy (often requiring torch/transformers), so I wrote this lightweight, zero-dependency library to solve it. It includes strategies for context packing, PII redaction, and tool output compression. Benchmarks show it can save ~15% of tokens with negligible latency overhead (<0.5ms). Happy to answer any questions!
Dec 2025 · github.com
- 24IB
After fine-tuning GPT for a personal project, I realized how tedious it is to write plain text in a massive JSON file. That's why I built this app for my own use, and I want to see if others could benefit from a tool like this as well ;)
2024 · finetuna-ui.com
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