Alternatives
Products that do what Vpuna AI Search – A semantic search platform does
Dear HN Community, I am a long time fan and first-time contributor. I just launched a developer focused semantic search platform and wanted to share it with the community. The idea is simple: upload structured or unstructured documents, select the fields you want to index and tag as metadata, and instantly get a clean search API you can use in your own app. Here is what it currently supports: - Manage your own tenants and projects - Upload .json and .txt files (support for .pdf, .docx, .xlsx, .yml, etc. coming soon) - Expose 3 APIs: search, upload document (embeddings), and delete document -…
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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
- 5SB
Hey HN! My brothers and I have worked on this for the last 2 weeks. We use OpenAI's `text-embedding-ada-002` model to embed queries and a vector database to search for similar verses / blocks of verses. We'd like to see what you think and appreciate any feedback!
2023 · siliconscripture.org
- 6IM
When your embedding provider is good, but could be better for your use-case.
2024 · zoplabs.com
- 7IM
AI search results are quickly becoming more important than SEO, but as businesses, we have no visibility over it! That's why I'm building "Ahrefs for AI search results". Track keyword performance on AI tools like ChatGPT, Claude, Perplexity & more
2025 · linrush.com
- 8SS
I built https://ask.rivestack.io — a semantic search engine over Hacker News posts. Instead of keyword matching, it finds results by meaning, so you can search things like "best way to handle authentication in microservices" and get relevant threads even if they don't contain those exact words. How it works: Indexed HN posts and comments into PostgreSQL with pgvector (HNSW index) Embeddings generated with OpenAI's embedding model Queries run as nearest-neighbor vector searches — typical response under 50ms The whole thing runs on a single Postgres instance, no separate vector DB I…
Feb 2026 · ask.rivestack.io
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Hello HN, We would like to present to you an advanced News API, that allows you to easily retrieve and process news articles from thousands of sources in different languages all over the world. Since our last submission, we have rewritten the project from scratch with a focus on cleansing and structuring the news data. Some of the advanced features of the new API: - clustering news articles into groups of related news - allows to detect news stories and assess how important / popular they are - detecting reprints and wired articles - allows to easily filter noise and get unique articles…
2022 · goperigon.com
- 10AE
Hey folks, Elias here. Excited to unveil my latest project. Why I Built This: Traditional keyword search isn't cutting it. I've used LLM-embeddings to provide more nuanced, relevant results. How It Works: LLM-embedding similarity on curated datasets for semantically similar results. No need to iterate over keywords any more. Current Datasets: - YC Companies - Show HN Posts, - Ask HN Posts - ProductHunt Startups - Github Top 200k Repos Use Cases: - Validate a product idea's existence - Check if someone already Asked HN something - Have fun - search random terms and see what pops up Want to…
2023 · payperrun.com
- 11SS
Hello Hacker News! I built Sleuth, an open source search tool for your workspace. I originally started off with Slack but quickly learned that Confluence search is a well documented problem: https://twitter.com/beajammingh/status/1273742155731791872?s... Sleuth solves this problem using semantic search to find relevant Confluence pages and Slack messages for your query. You can ask Sleuth questions about HR policies, technical documentation, product decisions, and more. Sleuth is open source and can be self-hosted, although there are dependencies on OpenAI and…
2023 · github.com
- 12IB
After getting frustrated with macOS's Spotlight search, e.g., typing "driver license" doesn't give me anything unless the file name matches exactly, I thought, why not index my entire Documents folder? This way, I can find that one PDF or image buried deep in subfolders using natural language queries. So I built SmartSearch; it uses SentenceTransformers for embeddings and FAISS for fast similarity search. Best of all, it runs locally on your computer. Github: https://github.com/neberej/smart-search/ Demo:…
2025 · github.com
- 13IB
Hi HN, For the last 18 months, I've been working solo on building a completely independent search engine from scratch. Today, I'm opening it up for beta testing and would love to get your feedback. The project powers two public sites from the same 2-billion-page index: Searcha.Page: A session-aware search engine that uses a persistent browser key (not a cookie) for better context. Seek.Ninja: A 100% stateless, privacy-first version with no identifiers at all. The entire stack is self-hosted on a single ~$4k bare-metal EPYC server in my laundry room (no cloud, no VC funding). The search…
2025
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Hi HN, I'm Daniel from Superlinked! We have built an open-source framework that improves vector search relevance and usefulness by combining structured metadata with unstructured data in your embeddings. We included self-hostable API server that sits between your data sources and vector database. Docs: https://docs.superlinked.com/ We're launching our cloud offering soon where you can use Superlinked to orchestrate high-performance retrieval for RAG, Search & Recommendation apps in your own cloud. Looking for feedback and happy to answer questions!
2024 · github.com
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Hi HN, We are building a search engine to help founders, investors, and early adopters to easily discover startups from all over the world. Discovering startups - whether it is a potential competitor, to validate an idea or as part of a DD process - is a difficult and time-consuming process. We believe that many existing platforms require expensive subscriptions and general-purpose search engines often do not give a complete enough picture. To solve this problem, we are releasing a free-to-use search engine (with a relatively generous daily limit on search volume). No sign-up is required. We…
2023 · symonda.com
- 16OS
Introducing Nia Vault, a CLI that lets you query your local markdown/text files using natural language. What it does: Semantic search over local folders and notes Works across multiple synced directories RAG-style answers with citations from your own files How it works: Calls `POST /search/query` with `local_folders` Uses `search_mode: sources` to return answers + file references Example: vault ask "What are my notes about project planning?" OSS: https://github.com/chenxin-yan/nia-vault
Feb 2026 · github.com
- 17HA
Hi all, I find literature searches to be slow and despite all the tools nowadays, it is difficult to map out vast areas of research and then connect my ideas to what I’m trying to do (e.g. writing a review, learning something new, planning a new project, assignments, etc). Some of my peers and teachers also found this to be a problem so I built this MVP app to help people not only leverage AI search capabilities but also go on to connect their ideas, map out research projects, cite various results and organise their “stream of consciousness” as they work. I’d love to get some feedback on it…
2025 · hexle.ai
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Tired of ads and misinformation clogging up your search results when you just want to see the science? That's why we built Consensus, a new search engine that uses Large Language Models to surface findings straight from scientific research for any question. If you like the product, please support our launch on Product Hunt today: https://www.producthunt.com/posts/consensus-2
2022 · consensus.app
- 19DR
The first ever AI peer reviewed research article just got approved. It’s kinda crazy how advanced AI have come to replace researchers. I've just been using Deep Research on ChatGPT and Perplexity a lot to write and research complex technical reports for my boss. He loves the reports and it has decreased my workload a ton but I still have some frustrations with it. None of them provide an API that gets me the same quality of output you would with the applications. I wanted something with more control on the LLMs, swappable with the reasoning new models that came out. Not just prompt →…
2025 · github.com
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Hi everyone, I read HN every day, but there was always more great content than I had time to read. I know there are already several HN summarizers on GitHub, and I tried some of them. They just didn't fit the workflow I wanted, so I decided to build my own. My project is a self-hosted app that automatically fetches top stories, summarizes them with AI, translates them into your preferred language, and prepares a personalized daily briefing in a nice customizable UI while you sleep. Maybe I'm not the only one who wanted this kind of workflow. I'd love to hear your thoughts, especially on what…
Jul 2026 · github.com
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I built InsideStack to make it easier to find high-quality technical and software articles. Why? - The web is flooded with AI-generated content - Businesses are publishing tons of articles with biased content - Search results are often driven by engagement rather than quality. - AI-generated summaries of articles don’t drive traffic back to the original creators InsideStack lets you: - Search across curated RSS feeds with semantic search - Subscribe, bookmark, and follow topics or authors Currently, only a small set of feeds is included, but I am adding more every day. Suggestions for…
Dec 2025 · insidestack.it
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Since managing the Large Language Models in production might be challenging, we've made a short demo to present how to use Cohere co.embed API and Qdrant Cloud to create a semantic QA system. This is based on bi-encoder architecture, and can be easily adopted to a different use case, like semantic search in any domain.
2022 · qdrant.tech
- 23DE
Hi HN! I built Docuglean, an open-source SDK for intelligent document processing that works with OpenAI, Mistral, Google Gemini, and Hugging Face models. The idea came from repeatedly writing boilerplate code to extract structured data from invoices, receipts, and other documents. Instead of wrestling with different API formats, I wanted a unified interface that: - Extracts structured data using Zod/Pydantic schemas - Classifies and splits multi-section documents (e.g., medical records) - Processes documents in batches with automatic error handling - Works locally without APIs (for…
Nov 2025 · github.com
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Hello HN! Sharing a pet project of mine. It started out as a dull photo-gallery then I tried to make it "smarter". In the process of development, I've learnt a lot about computer vision and programming in general. Current features: Search by tags (supports logical expressions, https://scenery.cx/search_syntax) Semantic text search You can find images with similar tags, color palette or visuals/semantics Reverse image search Image anti-duplication mechanism Automatic image tagging and captioning IPFS support…
2022 · scenery.cx
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