Alternatives
Products that do what Moss – AI-Powered Semantic Search Running In-Browser (No Cloud) does
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…
- 1
- 2
- 3
- 4
- 5
- 6
- 7SC
2020 · github.com
- 8
- 9VA
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
- 10
- 11SP
I was recently playing with Apple's CoreML and had several painful observations on tooling. It's not enough for a long read but should be for an HN post. In short, you can take a simple BERT-like encoder model in PyTorch, convert it into an f32 CoreML checkpoint, and run it on CPU or GPU, but not NPU. Let's unpack this. Having a simple and extensible format to exchange common ANN architectures is a big issue for anyone who uses more than one framework or programming language to run the same model. ONNX is the closest we have to that standard, but it's hard to call anything Protobuf-related…
2024 · github.com
- 12JO
2021 · 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
- 14OS
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
- 15UI
Hey everyone! I am excited to share updates on four of my & my teams' open-source projects that take large-scale search systems to the next level: USearch, UForm, UCall, and StringZilla. These projects are designed to work seamlessly together, end-to-end—covering everything from indexing and AI to storage and networking. And yeah, they're optimized for x86 AVX2/512 and Arm NEON/SVE hardware. USearch [1]: Think of it as Meta FAISS on steroids. It's now quicker, supports clustering of any granularity, and offers multi-index lookups. Plus, it's got more native bindings than probably…
2023 · usearch-images.com
- 16IM
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
- 17AE
Anchor Engine is ground truth for personal and business AI. A lightweight, local-first memory layer that lets LLMs retrieve answers from your actual data—not hallucinations. Every response is traceable, every policy enforced. Runs in <3GB RAM. No cloud, no drift, no guessing. Your AI's anchor to reality. We built Anchor Engine because LLMs have no persistent memory. Every conversation is a fresh start—yesterday's discussion, last week's project notes, even context from another tab—all gone. Context windows help, but they're ephemeral and expensive. The STAR algorithm (Semantic Traversal And…
Mar 2026 · github.com
- 18WB
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
- 19SS
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
- 20WA
Witchcraft is from-scratch Rust reimplementation of Stanford's XTR-Warp (SIGIR'25, https://arxiv.org/abs/2501.17788 ) multi-vector semantic search engine. Witchcraft runs out of a single SQLite database, is blazing-fast (21ms p.95 end-to-end search latency on NFCorpus on a MacBook Pro), accurate (33% NDCG@10), and easy to deploy in your own apps. The Witchcraft repo also comes with Pickbrain, a sample app and agent skill that you can use to instantly query across all your Claude Code and Codex CLI sessions, effectively giving your agents global long-term memory. Please…
Apr 2026 · github.com
- 21IE
Hey HN, when building ML systems for industrial AI, we have learned that data inspection is critical during the ML development process. We are also big fans of the Hugging Face ecosystem. That is why we built an integration to our data exploration tool Spotlight that allows you to interactively explore Hugging Face datasets with one line of code. Spotlight lets you leverage model results such as predictions and embeddings to gain a deeper understanding in data segments and model failure modes. Currently, many many NLP, CV, Audio and multimodal datasets are supported both locally and on the…
2023 · huggingface.co
- 22WB
Hi HN, I recently launched Wool Ball (https://woolball.xyz), a project designed to test the concept of paying people to enable their devices to process AI tasks through their browsers. The idea revolves around “browser as a service” or “browser as a server,” leveraging idle browser resources to create a decentralized, scalable, and cost-effective way to run AI workloads. We’re still in the early stages, and I’d love to hear your feedback on the concept and the product we’re building. Overview: https://woolball.xyz/Guide What do you think of this approach to…
2024
- 23BL
Hello everyone! I am Jan, CTO and one of the creators of Pathway, the real-time data processing framework. I’m excited to share Pathway’s ready-to-use AI Pipelines, configurable with just YAML! These frameworks offer out-of-the-box solutions for AI search, RAG, and more—optimized for real-time indexing and in-memory processing. What makes it simple? YAML templates! The pipeline templates are fully customizable using YAMLs to fit your needs, from changing the data sources to the choice of the LLM model, all without touching Pathway’s Python code. Thanks to the Pathway data processing engine,…
2024 · pathway.com
- 24IF
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
Ranked by how close each launch is in meaning, then by votes. Refine with a description →