Alternatives
Products that do what The Alexandria Index does
Massive internet datasets, embedded, open-sourced and free
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Hi HN! I am Maria, solo founder of DataQA (https://dataqa.ai/), a tool to search and label documents for various NLP tasks (e.g. entity extraction, entity linking, etc). I have worked as a data scientist and ML engineer for the better part of a decade, and over that time have specialised mainly in applications involving natural language processing (NLP). One of the key questions I have always had at the back of my mind is whether my time was well spent. Whenever I spent more time on feature engineering or trying different models, I always wondered whether I would get better…
2021
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I've always felt it a bit hard to grasp how far news reach and all. Because I'm also a bit behind on python, I decided to build something from scratch. It's really simple: docker compose, micro services connected to some very basic data pipelines using rabbitMQ, and some local NLP. The NLP portion is a bit slow as it's pure CPU and doesn't leverage GPU/NPE if you have them. The tool offers you to define your own "labels" and "relations", which are then picked up by the local NLP models to assign it to news articles. Standard, there are only a few included. But the goal is to have your…
Mar 2026 · github.com
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2013 · insightdatascience.com
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2020 · github.com
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Today you can easily adopt AI coding tools because you have git for branching and rolling back if AI writes bad code. We haven't seen this same capability for data and decided to build it ourselves. Nile is a new kind of data lake, purpose built for using with AI. It can act as your data engineer or data analyst creating new tables and rolling back bad changes in seconds. We support real versions for data, schema, and ETL. We'd love your feedback on any part of what we are building - https://getnile.ai/ What do you think?
Jan 2026
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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
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2015 · grid.ac
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Hi HN. Peter here. As a machine learning engineer, I mostly think in terms of feature vectors, embeddings, and matrices. One of the most useful byproducts of deep neural networks is embeddings because they allow us to represent high-dimensional data in terms of lower-dimensional latent vectors. These feature vectors can be used for downstream applications like similarly search, recommendation systems and near duplicate detection. As an ML engineer, I was frustrated by the lack of a datastore in which vectors are first-class citizens. As a result, most ML engineers, including myself, end up…
2021
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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! I am an undergrad student trying to build interesting things with AI. Recently, I was looking for a dataset I could use for a new project. I realized that it is really frustrating to go through all the government websites (with terrible UX) just to find some usable dataset. I set out to build a GitHub for datasets, named DataHub. Right now, we have more than 1000 datasets from Montréal and New York City, with more cities coming soon (and possible government agencies). All of this is wrapped into a powerful search. It's a breeze to find a dataset to work on. I'd be interested to know…
2017
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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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Hey HN community! Over the past year, AI copilots like Cursor and Windsurf have fueled a dramatic shift in software engineering workflows. And yet, many technical users in adjacent fields like data science and analytics have been unable to reap the rewards of this revolution. It turns out that the existing tools are a poor match for analytical workloads. Beyond that Cursor and similar tools have very poor support for Jupyter notebooks, data science is a fundamentally different discipline from software engineering and we believe it requires a correspondingly different tool. We're excited to…
Sep 2025 · sphinx.ai
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Hi HN, I wanted to share an exciting new open-source project: "VulcanSQL"! If you're interested in seamlessly transitioning your operational and analytical use cases from data warehouses and databases to the edge API server, this open-source data API framework might be just what you're looking for. VulcanSQL (https://vulcansql.com/) is suitable for following use cases: * Customer-facing analytics - expose analytics in your SaaS product for customers to understand how the product is performing for them via customer dashboards, insights, and reports. * Data Sharing - sharing…
2023 · vulcansql.com
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Hey HN! We just released the open-source version of Renumics Spotlight, a data exploration and analysis tool for multimodal datasets. Spotlight integrates seamlessly with pandas and supports rich data types like images, videos, and meshes. You can load anything that fits in a DataFrame and view it through a customizable GUI featuring multiple interactive widgets: a data table, similarity map, histograms, scatter plots, and more. In the past, we have used Spotlight for exploratory data analysis and tackling various model and data-related problems in our machine learning projects. What are…
2023 · renumics.com
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2022 · go.instill.tech
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Hey, OpenAI recently released "assistants" - These have RAG built into the API, which means that you can provide up to 10.000 files to the assistant without the overhead of dealing with vector databases, splitting files into chunks and more. They work surprisingly well, so I've built a free simple tool to embed them on websites. It has no dependencies and simply uses fetch to communicate to my backend which proxies openai. In the future I plan to add more widget embedding options (currently only chat is available). Let me know if you have any specific questions about either the tool or…
2024 · rispose.com
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Hey HN, Data quality matters more than ever. Our world increasingly relies on AI and proprietary datasets to fine-tune models. But as many of us know, garbage in often results in garbage out. Bad data can cost millions, especially when it informs important decisions like public health policy or interest rate hedging. Today’s data engineers need a flexible, secure, and performant data quality toolkit designed for the modern workflow. But current solutions were built a decade ago and don't support big data technologies, such as Spark. This is why we're building Spotlight - the data quality…
2023 · spotlight.dev
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