Alternatives
Products that do what Marqo does
Train and deploy embedding models
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We are a small group of undergrads interested in building human in the loop coding agents. We dream of a world where building complex agent workflows feels as simple and creative as playing with legos. When we were building stuff we needed a tool that made it easy to try out different code embedding models so that we could see which ones worked best in different scenarios and understand their strengths and weaknesses. So to speed that process up we made PurpleSearch an 'instant' search engine for your local codebases. This tool lets you quickly deploy any open source embedding model on…
2025
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2021 · github.com
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2020 · modelzoo.dev
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Introducing embeds.ai: an embedding playground to compare how embedding models work on a real world use case (retrieval augmented generation for Wikipedia articles + Elad Gil's High growth handbook) A few weeks ago, Shreyan and I were looking for an embedding model to use for RAG. We eventually came across the MTEB leaderboard, but we struggled to understand the benchmark scores. We wanted a tool to test various embedding models with example queries on real-world datasets. After unsuccessfully looking for such a “playground”, we decided to just build one ourselves! We embedded HuggingFace’s…
2023 · embeds.ai
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2020 · picsellia.com
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Hi HN! As someone who reads tons of blogs, I've always gravitated toward posts that let me click something, be it a simple quiz or even a mini-game or a simulation. There have never been many of such blogs since developing custom elements requires coding knowledge. I believe that's no longer the case in the AI era. I'm building a tool that allows you to create any interactive embed you can imagine by simply chatting with AI: * A quiz of any format and outcome: https://embedex.io/blog-demo#quiz-ai * A working drum machine:…
Sep 2025 · embedex.io
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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
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Hey HN! We're excited to launch https://depot.ai today - depot.ai is an open-source Docker registry that makes it easy to embed public models from Hugging Face in your Docker images using a `COPY`: # Copy all files from the model repo to the current WORKDIR COPY --link --from=depot.ai/runwayml/stable-diffusion-v1-5 / . # COPY just one file from the model repo to the current WORKDIR COPY --link --from=depot.ai/runwayml/stable-diffusion-v1-5 /v1-5-pruned.ckpt . To optimize build speed, cache hits, and registry storage, we're building each image…
2023
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Hi HN! We (Thomas and Stéphan, hello!) recently released Model2Vec, a Python library for distilling any sentence transformer into a small set of static embeddings. This makes inference with such a model up to 500x faster, and reduces model size by a factor of 15 (7.5M params or 15/30MB on disk, depending on whether you use float16 or float32). This allows you to embed 50-100k documents per second on a cpu on a macbook. This reduction of course comes at a cost: distilled models are worse than their parent models. Even so, they are actually a lot better than large sets of conventional…
2024 · github.com
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2019 · deploymachinelearning.com
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Hi there, I've created this side project to make it easier to find interesting repositories using AI. There's still a lot of work to be done to improve it, so any suggestions for enhancements would be greatly appreciated. Thank you!
2024 · awesome-repositories.com
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Marmot hits major milestone I've been solo pushing (with help of AI), to really mature out the system. And yesterday I have hit the first milestone where MySQL API is stable enough to make WordPress install and work flawlessly. System is now in a place where you can spin off a cluster, and then spin off many replicas you want to scale out. I wanted to build something that is actually hard with AI, and it's been long and tough journey trying various AI tools, and huge amount of learning. I will follow up with a blog post, but since I have all the scripts to help you guys spin up cluster and…
Dec 2025 · github.com
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Hi HN, My name is Othmane and I’ve been in the ML field (building and shipping models) for the last ~5years. Today, as many people out there, I come across new AI tools every week. However I was a bit surprised to see little to no mention of established AI vendors that existed before chatGPT and how most use cases are heavily biased toward content generation (text/image) or conversational AI (chatbots). I built a tool that helps you find the right AI solution/provider based on your use case. It uses a curated database of 100+ solutions from established vendors. It covers things…
2023 · preview.steerlab.ai
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User Embeddings lets you build user-intent AI agents, hyper-personalized semantic search, and bring up-to-date information to GenAI applications in a personalized way. Docs: https://firstbatch.gitbook.io/firstbatch-sdk/ If you are a YC company , you can get User Embeddings free for a year by signing up here: https://www.firstbatch.xyz/subscribe
2023 · userembeddings.firstbatch.xyz
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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
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2023 · github.com
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We open-sourced catsu, a Python client for embedding APIs. The problem: every embedding provider has a different SDK with different bugs. OpenAI has undocumented token limits. VoyageAI's retry logic was broken until September. Cohere breaks downstream libraries every release. LiteLLM's embedding support is minimal. catsu provides: - One API for 11 providers (OpenAI, Voyage, Cohere, Jina, Mistral, Gemini, etc.) - Bundled database of 50+ models with pricing, dimensions, and benchmark scores - Built-in retry with exponential backoff - Automatic cost tracking per request - Full async support…
Dec 2025 · catsu.dev
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Hi, I'm Ben, the co-creator of Embedbase. Embedbase lets you use OpenAI Embeddings and Pinecone seamlessly. For example, you can add Embedbase to your app and pair it with GPT3 to allow people to search using natural language (e.g. How many workouts did I complete last week?), or simply expanding your current search experience beyond full-text search (e.g. looking for "similar" documents in Notion to find other related information) Managing embeddings is uncharted territory, we needed to discover the best practices ourselves. Now we're happy to share our learnings with Embedbase. Shoot if…
2023 · embedbase.xyz
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