Alternatives
Products that do what I've been using AI to analyze every supplement on the market does
Hey HN! This has been my project for a few years now. I recently brought it back to life after taking a pause to focus on my studies. My goal with this project is to separate fluff from science when shopping for supplements. I am doing this in 3 steps: 1.) I index every supplement on the market (extract each ingredient, normalize by quantity) 2.) I index every research paper on supplementation (rank every claim by effect type and effect size) 3.) I link data between supplements and research papers Earlier last year, I took pause on a project because I've ran into a few issues: Legal: Shady…
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Prompt analytics and citation mapping for AI search
Jul 2026 · search-console.ai
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AI tool that scrapes and analyzes 1000s of data points from platforms like G2, Reddit, Twitter, and SEMrush to solve a major growth bottleneck: manual market research. The goal is to help marketers, startups, and product teams save time by automating competitive analysis, sentiment trends, and growth opportunity discovery. Instead of spending hours manually researching, you can get actionable insights in seconds. Free Trial : You can generate 1 free report.
2025 · rocktangle.com
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Evidence-based supplement advice from real PubMed studies
Jun 2026 · supplements-ai.vercel.app
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I built a web page that aggregates data about data center buildup, sovereign fund investments into AI and bottlenecks. The objective is to predict AI race cooldown by looking at a potential decrease of activity involving these elements. The website looks at the quarterly forms from the 5 biggest hyperscalers and adds their CapEx into the mix, calculating a composite index in the end showing how likely it is for the AI race to slow down. Enjoy!
Jul 2026 · laurentiugabriel.github.io
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Hey HN, we built an Econ+Finance database to let AI agents do investment research. We spend a lot of tokens to organize macro releases and SEC filings into a clean format, so that your agents have more context to do actual analysis. The problem AI agents are great at data analysis. But they become ineffective if most of their context window is spent on gathering and cleaning data, instead of validating hypotheses. Data in the wild is messy and rarely standardized. Definitions and measurements change over time. This problem is compounded by a fragmented data universe. Point solutions exist…
Jul 2026 · github.com
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How it works (tech stack): -Built entirely with Lovabl.dev (no-code front-end + logic) -ChatGPT / Claude for research and inspiration -Powered by GPT-4 Vision to interpret charts visually -Hosted on Supabase for performance & caching It’s not meant to replace analysts — just to speed up how traders interpret data. I’m a designer exploring AI tools, and this is my first attempt to turn an idea into a functional product. Would love to know what you think.
Oct 2025 · quantify-ai.co
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As a researcher, I created SmartXiv to solve a problem I faced every day: keeping up with the overwhelming number of research papers uploaded to arXiv. With over 1000 new papers each day, finding the most relevant research was time-consuming and exhausting. I needed a smarter way to stay updated. What SmartXiv Does • Personalized Recommendations: Using advanced AI, SmartXiv analyzes your interests and sends you daily emails with research papers that align with your preferences. •Efficient Research: By curating the latest papers for you, SmartXiv saves you hours of research. • Fully…
2024 · smartxiv.com
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