Alternatives
Products that do what VIGILATE does
Legal document summarizer. No jargon, just simple english
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Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…
2023 · github.com
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I made this because I think that if contracts were written in plain text files and managed more like software, from version control to IDEs, lawyers would work more quickly and intelligently for their clients, saving them money. But the entire practice of transactional law is stuck on Microsoft Word. My clients are mostly technology companies with an appetite for innovation. With their encouragement, I am moving my own legal practice away from formats like Microsoft Word and into plain text. Electronic signatures of plain text contracts is the starting point for that effort. The MVP is this…
2022 · magistrate.khanna.law
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88% of people never read the terms and conditions of websites or services they use. However, most people want to know what they are agreeing to in those terms. That is why we created Legal Leaf. We strongly believe that everyone should have easy access to those agreements, in language they can understand. Legal Leaf works behind the scenes, in your browser, to read and summarize these terms using powerful AI. We're constantly working to improve the accuracy of these summaries. The results are displayed in the top right corner without affecting web speeds. Legal Leaf is a beta product still…
2018
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2011 · doccompare.com
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Hi HackerNews, Lately, I have seen an explosion in posts offering paid APIs/services to get unstructured data into LLMs (i.e. langchain extract, ragflow, unstructured, unstract, just to name a few) and I have been largely disappointed by them, either because they fail to implement multimodal support, fail to give good context for "really tricky" PDFs / Word docs / Powerpoints, or are just plain difficult to use. In light of all these posts I figured I'd share my solution that has been working smoothly for me and my clients. I put it up on GitHub for free so you can check it…
2024 · github.com
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I'm excited to share a project. It's a Python script that utilizes the LangChain framework and the ChatOllama model to generate concise summaries from webpages and YouTube videos. For those preferring a graphical interface, it includes a Gradio app that runs in the browser to use the summarizer interactively. Easily containerize and deploy the summarizer with Docker. The tool is perfect for anyone needing quick insights without reading through the entire content/ It's open for contributions, so if you're interested in improving or extending its functionalities, feel free to dive in!
2024 · github.com
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2018 · github.com
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