Alternatives
Products that do what KRAG does
Simplifying Last Mile Reporting
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Hey there HN! We’re Antonio, Luca, and Yuhang, and we’re excited to introduce Fast GraphRAG, an open-source RAG approach that leverages knowledge graphs and the 25 years old PageRank for better information retrieval and reasoning. Building a good RAG pipeline these days takes a lot of manual optimizations. Most engineers intuitively start from naive RAG: throw everything in a vector database and hope that semantic search is powerful enough. This can work for use cases where accuracy isn’t too important and hallucinations are tolerable, but it doesn’t work for more difficult queries that…
2024 · github.com
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Hey HN, I’m Zach from Superpowered AI (YC S22). We’ve been working in the RAG space for a little over a year now, and we’ve recently decided to open-source all of our core retrieval tech. spRAG is a retrieval system that’s designed to handle complex real-world queries over dense text, like legal documents and financial reports. As far as we know, it produces the most accurate and reliable results of any RAG system for these kinds of tasks. For example, on FinanceBench, which is an especially challenging open-book financial question answering benchmark, spRAG gets 83% of questions correct,…
2024 · github.com
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Query data to build dashboards and generate detailed reports
Apr 2026 · orcasheets.ai
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2023 · gist.github.com
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I built a tool called *Kekkai* for file integrity monitoring in production environments. It records file hashes during deployment and later verifies them to detect unauthorized modifications (e.g. from OS command injection or tampering). Why it matters: * Many web apps (PHP, Ruby, Python, etc.) on AWS EC2 need a lightweight way to confirm their code hasn’t been changed. * Traditional approaches that rely on metadata often create false positives. * Kekkai checks only file content, so it reliably detects real changes. * I’ve deployed it to an EC2 PHP application in production, and it’s working…
Sep 2025 · github.com
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- Discovering the most effective RAG pipeline for your specific data and use case can be daunting. It requires experimenting with various RAG modules and configurations, which are both time-consuming and complex. - AutoRAG addresses this challenge by automatically evaluating different combinations of RAG modules and their parameters. You don't need to write implementation code yourself; everything is set up through a single YAML file. - Our aim is to save you the hassle of continuously adapting to new RAG modules and configurations. Instead, you can focus on developing robust data for your…
2024 · github.com
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Hi HN, I have been working with regulation-heavy documents lately, and one thing kept bothering me. Flat RAG pipelines often fail to retrieve related articles together, even when they are clearly connected through references, definitions, or clauses. After trying several RAG setups, I subjectively felt that GraphRAG was a better mental model for this kind of data. The Microsoft GraphRAG paper and reference implementation were helpful starting points. However, in practice, I found one recurring friction point: graph storage and vector indexing are usually handled by separate systems, which…
Jan 2026 · github.com
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In my previous role at a small startup, I frequently developed simple scripts to assist recruiters and marketing professionals in handling data processing tasks on Excel or CSV files. These tasks were typically straightforward and repetitive, stemming from the periodic export of data. This experience sparked the idea to create a straightforward tool dedicated to such functionalities(also mobile friendly, as they occasionally need to process data on their smartphones). There are powerful tools like Power Query and Tableau, but they often prove too complex for non-technical users to navigate…
2024 · tablesmith.io
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2015 · github.com
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I built CSV GB+ by Data.olllo, a local data tool that lets you open, clean, and export gigabyte-sized CSVs (even billions of rows) without writing code. Most spreadsheet apps choke on big files. Coding in pandas or Polars works—but not everyone wants to write scripts just to filter or merge CSVs. CSV GB+ gives you a fast, point-and-click interface built on dual backends (memory-optimized or disk-backed) so you can process huge datasets offline. Key Features: Handles massive CSVs with ease — merge, split, dedup, filter, batch export Smart engine switch: disk-based "V Core" or RAM-based "P…
2025 · apps.microsoft.com
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