Alternatives
Products that do what Alcove - Local Semantic Search does
Index your world. Share it with the universe. Plugins for HF
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2023 · github.com
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Sep 2025 · github.com
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Hi HN, I built an open-source AI agent that has already indexed and can search the entire Epstein files, roughly 100M words of publicly released documents. The goal was simple: make a large, messy corpus of PDFs and text files immediately searchable in a precise way, without relying on keyword search or bloated prompts. What it does: - The full dataset is already indexed - You can ask natural language questions - Answers are grounded and include direct references to source documents - Supports both exact text lookup and semantic search Discussion around these files is often fragmented. This…
Jan 2026 · epstein.trynia.ai
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Interactive demo: https://getcanary.dev/docs/cloud/demo Canary works with local search indexes like Pagefind too: https://getcanary.dev/docs/local/demo For both demo, you'll find small "code" tab to see actual code to build the search UI. Self-hosting guide: https://getcanary.dev/docs/cloud/self-host Would love to hear any feedback!
2024 · github.com
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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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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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Hi HN! I'm the author of mere.run a local first inference runtime built around an installable CLI. I believe that whenever possible we should use the stuff we already own (like our Mac laptops, decent machines gathering dust, our gaming PC) and the limited electrical power we have easy access to, like the socket in the wall next to most of us. We shouldn't have to send our data to the cloud hoping some T&C will prevent it from being used in a way that we'd regret. Most of the local AI solutions are technical, involved, and land a curious body in some package hell. People are optimizing for…
Jul 2026 · github.com
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Hi HN, I am Anubhav from Ramanlabs. We have been working on a native gui application to allow users to search any video data( mp4, mkv) or video streams (http/rtsp) using computer vision. Application is supposed to work like a video player which displays decoded frames and recognizes objects concurrently, making it an interactive experience. It works in super real-time and only expects a quad-core CPU with AVX2 instructions at minimum. Application is free to download (without any signup/account). We are only supporting WINDOWS for now [0]. Even though this is a binary application,…
2022 · ramanlabs.in
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2023 · github.com
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I got tired of the overhead required to run even a simple data analysis - cloud setup, ETL pipelines, orchestration, cost monitoring - so I built a fully local data-stack/IDE where I can write SQL/Py, run it, see results, and iterate quickly and interactively. You get data lake like catalog, zero-ETL, lineage, versioning, and analytics running entirely on your machine. You can import from a database, webpage, CSV, etc. and query in natural language or do your own work in SQL/Pyspark. Connect to local models like Gemma or cloud LLMs like Claude for querying and analysis. You…
Apr 2026 · stream-sock-3f5.notion.site
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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
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I wanted a file management tool that actually understands what my files are about. Previous projects like LlamaFS (https://github.com/iyaja/llama-fs) aren't 100% local and require an AI API. So, I created a Python script that leverages AI to organize local files, running entirely on your device for complete privacy. It uses Google Gemma2 2B and llava-v1.6-vicuna-7b models for processing. Note: You won't need any API key and internet connection to run this project, it runs models entirely on your device. What it does: - Scans a specified input directory for files -…
2024 · github.com
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Mar 2026 · llamaindex.ai
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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
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