Alternatives
Products that do what Semantic Search for Confluence Workspace does
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…
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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 -…
2025 · aisearch.vpuna.com
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I built this because I got tired of watching Claude Code read through massive files just to find a few functions. Sourcerer lets AI agents search code semantically and grab exactly the code chunks they need instead of burning tokens on whole files. It uses tree-sitter to parse your codebase and creates a searchable index. So instead of "read auth.py (538 lines)", an agent can search for "user authentication logic" and get back just the relevant functions. Demo: https://asciinema.org/a/736638 GitHub: https://github.com/st3v3nmw/sourcerer-mcp
2025 · github.com
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2016 · appbaseio.github.io
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2018 · typesense.org
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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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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
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Author here. Got tired of checking Upwork, NoFluffJobs, eFinancialCareers, LinkedIn and HN threads separately, so I built a CLI that scrapes them into a local SQLite DB and lets me browse everything in one web UI with filters and semantic search. Details: - Scraping via real browser over CDP (your own logged-in session, no API keys) - Embeddings run locally (nomic-embed-text via fastembed), stored in Lance - Rust backend, SolidJS frontend embedded in binary, single static executable Works for my use case (Europe-based contractor). It's my first rust project, decided to do local CLI, it's…
Jul 2026 · github.com
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Hey Hacker News, We've been working on ways to save people time at work and we've got something for you to try that we think can do just that. Pensieve lets you search across silos from one safe, convenient place, and save and retrieve notes without disturbing your workflow. Check it out at https://www.pensieve.ai, or on Youtube at https://youtu.be/-lQLmVSRI6Q.
2018
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2015 · hackersearch.io
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2017 · wearedomino.com
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I vibe-coded a small project that turns the “Ask HN: Who is hiring?” thread into searchable job data using OpenAI, PostgreSQL, and Metabase. It pulls the thread using the Hacker News API, uses GPT to extract fields like company, role, location, salary, and contact, stores everything in PostgreSQL, and spins up Metabase so you can explore and search the results. Right now it runs locally, but would anyone be interested if I built this out a bit more and made a public dashboard?
2025 · github.com
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I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!
Sep 2025 · infrastructureas.ai
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When your embedding provider is good, but could be better for your use-case.
2024 · zoplabs.com
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I'm Tyler - the solo operator of Quanta Intellect based in Portland, Oregon. I recently participated in Nous Research's Hermes Agent Hackathon, which is where this project was born. I've used agents extensively in my workflows for the better part of the last year - the biggest pain point was always the browser. Every tool out there assumes a human operator with automation bolted on. I wanted to flip that - make the agent the primary driver and give the human a supervisory role. Enter: Vessel Browser - an Electron-based browser with 40+ MCP-native tools, persistent sessions that survive…
Mar 2026 · quantaintellect.com
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Last night, OpenAI launched Deep Research, a tool for AI-powered deep web searches. In a few hours, I built an open-source alternative using Next.js, Firecrawl, and Vercel's AI SDK. Instead of using a fine-tuned version of o3, this method uses Firecrawl's extract + search with a reasoning model to deep research the web. The system is built using Vercel’s AI SDK for handling requests and streaming data, with an agent-based approach that manages search, extraction, and analysis. It uses Firecrawl to find and extract structured data, which is then processed through a progressive analysis system…
2025 · github.com
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Hi HN, I'm one of the creators of Nanobrowser, an open-source Chrome extension that lets you automate web tasks using AI agents. We were inspired by the potential of tools like OpenAI's Operator, but we wanted something that was: -Open-Source:You can see the code, modify it, and contribute to the project. -Browser-Based:No complex setups or server deployments. It runs directly in your browser. -Customizable:You can tailor the agent's behavior to your specific needs. -BYO LLM:Bring your own large language model API key (OpenAI, Anthropic,or even local models), No vendor lock-in. -Privacy…
2025 · github.com
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We’re George and Ann, and want to share a Hacker News specific browser extension that we have been working on. We all love the rich discussions in HN, but navigating long posts with multiple threads can sometimes be challenging. You get lost in the depth and breadth of the discussion. There are a few AI-based summarization tools, but they typically focus on summarizing the article rather than the comments, and thus miss the essence of threaded discussions. So, we built Hacker News Companion, a browser extension that makes it easy to navigate discussions and understand diverse viewpoints…
2024 · github.com
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I built TraceAIO, an open-source tool that prompts LLMs on your behalf and tells you whether ChatGPT, Perplexity, and Gemini mention your brand — and which competitors and sources show up instead. Yeah, this category smells a bit like a grift, same as early SEO. And I think over time it will become just SEO again, and become about good content. The tool just helps you monitor over time. It queries the browser products through real browser sessions, not APIs, runs on Docker, with an MCP server so you can query your own data through an LLM. No business model, Apache 2.0, self hosted. If you…
Jun 2026 · traceaio.org
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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
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