Alternatives
Products that do what Graphthem does
Deep-research engine reads 10,000 articles, gives one answer
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Hey HN, I'm excited to introduce Graphthem, a search engine designed to explore the deeper layers of knowledge rather than just surface-level popularity. While many AI search engines simply summarize top N results, we've found this approach often misses the many good stuff that is buried deeper in the links and references. Graphthem takes a different approach. we don't just look at the first few pages we find. We also dig into what those pages link to, so you get the whole story. This allows us to deliver answers that capture not just what's immediately visible, but also the foundational…
2024 · graphthem.com
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2021 · hacker-recommended-books.vercel.app
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Understanding scientific articles can be tough, even in your own field. Trying to comprehend articles from others? Good luck. Enter, Now I Get It! I made this app for curious people. Simply upload an article and after a few minutes you'll have an interactive web page showcasing the highlights. Generated pages are stored in the cloud and can be viewed from a gallery. Now I Get It! uses the best LLMs out there, which means the app will improve as AI improves. Free for now - it's capped at 20 articles per day so I don't burn cash. A few things I (and maybe you will) find interesting: * This is…
Feb 2026 · nowigetit.us
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Factually accurate articles with citations, up to 5000 words
2024 · writesonic.com
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I built a system that monitors ~200,000 news RSS feeds in near real-time and clusters related articles to show how stories spread across the web. It uses Snowflake’s Arctic model for embeddings and HNSW for fast similarity search. Each “story cluster” shows who published first, how fast it propagated, and how the narrative evolved as more outlets picked it up. Would love feedback on the architecture, scaling approach, and any ways to make the clusters more accurate or useful. Live demo: https://yandori.io/news-flow/
Nov 2025 · yandori.io
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Hi HN! My latest side project is knowledge graph that maps the French culinary network using data extracted from restaurant reviews from LeFooding.com. The project uses LLMs to extract structured information from unstructured text. Some technical aspects you may be interested in: - Used structured generation to reliably parse unstructured text into a consistent schema - Tested multiple models (Mistral-7B-v0.3, Llama3.2-3B, gpt4o-mini) for information extraction - Created an interactive visualization using gephi-lite and Retina (WebGL) - Built (with Claude) a simple Flask web app to clean and…
2025 · theophilecantelob.re
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2021 · deephn.org
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Hey HN! We're Paul, Preston, and Daniel from Zep. We've just open-sourced Graphiti, a Python library for building temporal Knowledge Graphs using LLMs. Graphiti helps you create and query graphs that evolve over time. Knowledge Graphs have been explored extensively for information retrieval. What makes Graphiti unique is its ability to build a knowledge graph while handling changing relationships and maintaining historical context. At Zep, we build a memory layer for LLM applications. Developers use Zep to recall relevant user information from past conversations without including the entire…
2024 · github.com
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2022 · prashantbarahi.com.np
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We can now build drastically higher quality search because we can use LLMs in algorithms that mimic a human's systematic research process, instead of just roughly recommending results based on semantic embeddings or term frequency. We built a deep search LLM pipeline that takes a few minutes to carefully search all the scientific literature. You describe your complex goal, as you would to a colleague. Then, we carefully search 200M+ papers. We classify the preliminary results with GPT-4. We then adapt the search goals based on relevant/irrelevant papers uncovered and continue searching,…
2024 · undermind.ai
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We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of…
2025 · blog.kuzudb.com
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Get instant insights about the topic you're reading about
Feb 2026 · whatsupwiththat.app
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We (Nick, Dens, Denzell, Fede, Drew, Aaryan, and Daniel) have been building HN Discovery, a discovery-focused search engine for Hacker News, in our spare time for the past 6 months and are excited to show it! It adds the following features relative to the existing keyword search interface and preserves the existing ones: - no-JS version (hnnojs.trieve.ai) - site:{required_site} and site:{negated-site} filters - public analytics - LLM generated query suggestions based on random stories - recommendations - dense vector semantic search - SPLADE fulltext search - RAG AI chat - order by…
2024 · hn.trieve.ai
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Small experiment of visualization of wikipedia articles as a graph using d3.js.<p>Articles with more traffic are bigger. I computed the semantic similarity using LSI with python (gensim) You have to scroll down/right a bit!<p>http://similarityapi.appspot.com/graph/?title=blade%20runner<p>There is also a JSON api: http://similarityapi.appspot.com/api/v1/?limit=100&title=blade%20runner<p>All feedback is appreciated:<p>@lucamartinetti [email protected]
2012 · similarityapi.appspot.com
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