Best AI tools for< Research Case Law >

LawDroid is an AI legal assistant application designed to help legal professionals work smarter and more efficiently. It serves as a force multiplier, enabling users to accomplish more tasks without additional overhead. LawDroid offers features such as case law research, drafting emails and letters, and document analysis. It also provides benefits like intake new clients, data-driven decisions, automate documents, human in the loop automation, and building scalable tools. The application is used by students, faculty, and legal professionals to streamline legal processes and improve client experiences.

AI Lawyer is a personal AI legal assistant that provides legal research, document handling, and other legal services to consumers, lawyers, and law students. It is designed to make legal services more accessible and affordable, and to help users understand and navigate the legal system. AI Lawyer is available online, on iOS, and on Android.

Paxton is an advanced AI platform designed to support legal and business professionals by automating and enhancing tasks such as contract review, legal drafting, and document analysis. Utilizing state-of-the-art artificial intelligence, including proprietary Legal Language Models, Paxton streamlines complex legal processes, improves accuracy, and drives efficiency across a wide range of applications.

Blue J is a legal technology company founded in 2015, dedicated to enhancing tax research with the power of AI. Their AI-powered tool, Ask Blue J, provides fast and verifiable answers to tax questions, enabling tax professionals to work more efficiently. Blue J's generative AI technology helps users find authoritative sources quickly, expedite drafting processes, and cater to junior staff's research needs. The tool is trusted by hundreds of leading firms and offers a comprehensive database of curated tax content.

Ask Blue J is a generative AI tool designed specifically for tax experts. It provides fast, verifiable answers to complex tax questions, helping professionals work smarter and more efficiently. With its extensive database of curated tax content and industry-leading AI technology, Ask Blue J enables users to conduct efficient research, expedite drafting, and enhance their overall productivity.

Legal Assist AI is an industry-leading startup that offers cutting-edge, AI-driven services to revolutionize the legal landscape. Founded by James Bratton, the platform provides automated contract analysis, intelligent case management systems, and predictive analytics tailored for the legal profession. With a vision to redefine efficiency and elevate the quality of legal services, Legal Assist AI aims to transform the future of legal work through innovative AI technology.

LawBotica is an AI-powered platform that revolutionizes legal work by automating deposition summaries, crafting case timelines, offering comprehensive due diligence, document review, interactive chats, and collaborative workspaces. It transforms legal practice, turning months of work into minutes of efficiency. LawBotica empowers legal teams with AI-powered modules for document review, summarization, chat, repository management, and case assessment. It provides personalized solutions for legal practices, versatile deployment options, and a flexible API for custom integration.

Legal Assist AI is an industry-leading startup founded by James Bratton, offering cutting-edge, AI-driven services such as automated contract analysis, intelligent case management systems, and predictive analytics tailored for the legal profession. With a vision to transform the legal landscape, Legal Assist AI redefines efficiency and elevates the quality of legal services through innovative solutions.

Lexicore is an AI tool designed specifically for legal practices. It utilizes advanced artificial intelligence algorithms to streamline and enhance various legal processes. By leveraging natural language processing and machine learning techniques, Lexicore offers efficient solutions for legal professionals to improve their workflow and decision-making. With its user-friendly interface and powerful capabilities, Lexicore aims to revolutionize the legal industry by providing cutting-edge AI technology tailored to meet the unique needs of legal practitioners.

Beebzi.AI is an all-in-one AI content creation platform that offers a wide array of tools for generating various types of content such as articles, blogs, emails, images, voiceovers, and more. The platform utilizes advanced AI technology and behavioral science to empower businesses and individuals in their marketing and sales endeavors. With features like AI Article Wizard, AI Room Designer, AI Landing Page Generator, and AI Code Generation, Beebzi.AI revolutionizes content creation by providing customizable templates, multiple language support, and real-time data insights. The platform also offers various subscription plans tailored for individual entrepreneurs, teams, and businesses, with flexible pricing models based on word count allocations. Beebzi.AI aims to streamline content creation processes, enhance productivity, and drive organic traffic through SEO-optimized content.

MIT Sloan Management Review is a leading source of information and ideas on management, innovation, and leadership. The website provides articles, case studies, videos, and podcasts on a wide range of topics, including artificial intelligence, data analytics, digital transformation, and sustainability. The website also offers a variety of resources for educators, students, and business professionals.

EssayAI is an AI-powered essay writing tool that helps users generate high-quality, plagiarism-free essays. It is designed to be undetectable by AI detectors and offers a range of features to assist writers, including smart outlining, extensive scholarly database integration, instant citation system, intelligent AI chatbot, and vast AI-driven toolsets. EssayAI can be used to write essays for various academic levels and subjects, as well as research papers, theses, case studies, and analytical reviews. It is also suitable for content writing freelancers and students who need help improving their writing skills.

The Generative AI in the Newsroom project is an effort to collaboratively figure out how and when (or when not) to use generative AI in news production. It includes articles, research, and case studies on the use of generative AI in journalism.

Snorkel AI is a data-centric AI application designed for enterprise use. It offers tools and platforms to programmatically label and curate data, accelerate AI development, and build high-quality generative AI applications. The application aims to help users develop AI models 100x faster by leveraging programmatic data operations and domain knowledge. Snorkel AI is known for its expertise in computer vision, data labeling, generative AI, and enterprise AI solutions. It provides resources, case studies, and research papers to support users in their AI development journey.

MagickSEO is an AI-powered SEO optimization tool that helps businesses improve their website's search engine performance. With insights from millions of case studies, MagickSEO provides tailored recommendations to enhance keyword relevance, content quality, and overall SEO structure. The tool's user-friendly interface and step-by-step guidance make it easy for businesses of all sizes to optimize their websites for better visibility and organic traffic.

Google Research is a leading research organization focusing on advancing science and artificial intelligence. They conduct research in various domains such as AI/ML foundations, responsible human-centric technology, science & societal impact, computing paradigms, and algorithms & optimization. Google Research aims to create an environment for diverse research across different time scales and levels of risk, driving advancements in computer science through fundamental and applied research. They publish hundreds of research papers annually, collaborate with the academic community, and work on projects that impact technology used by billions of people worldwide.

Google Research is a team of scientists and engineers working on a wide range of topics in computer science, including artificial intelligence, machine learning, and quantum computing. Our mission is to advance the state of the art in these fields and to develop new technologies that can benefit society. We publish hundreds of research papers each year and collaborate with researchers from around the world. Our work has led to the development of many new products and services, including Google Search, Google Translate, and Google Maps.

The Google Research Blog is a platform for researchers at Google to share their latest work in artificial intelligence, machine learning, and other related fields. The blog covers a wide range of topics, from theoretical research to practical applications. The goal of the blog is to provide a forum for researchers to share their ideas and findings, and to foster collaboration between researchers at Google and around the world.

The Research Center Trustworthy Data Science and Security is a hub for interdisciplinary research focusing on building trust in artificial intelligence, machine learning, and cyber security. The center aims to develop trustworthy intelligent systems through research in trustworthy data analytics, explainable machine learning, and privacy-aware algorithms. By addressing the intersection of technological progress and social acceptance, the center seeks to enable private citizens to understand and trust technology in safety-critical applications.

Research Studio is a next-level UX research tool that helps you streamline your user research with AI-enhanced analysis. Whether you're a freelance UX designer, user researcher, or agency, Research Studio can help you get the insights you need to make better decisions about your products and services.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

This repository is dedicated to summarizing papers related to large language models with the field of law. It includes applications of large language models in legal tasks, legal agents, legal problems of large language models, data resources for large language models in law, law LLMs, and evaluation of large language models in the legal domain.

Lawyer LLaMA is a large language model that has been specifically trained on legal data, including Chinese laws, regulations, and case documents. It has been fine-tuned on a large dataset of legal questions and answers, enabling it to understand and respond to legal inquiries in a comprehensive and informative manner. Lawyer LLaMA is designed to assist legal professionals and individuals with a variety of law-related tasks, including: * **Legal research:** Quickly and efficiently search through vast amounts of legal information to find relevant laws, regulations, and case precedents. * **Legal analysis:** Analyze legal issues, identify potential legal risks, and provide insights on how to proceed. * **Document drafting:** Draft legal documents, such as contracts, pleadings, and legal opinions, with accuracy and precision. * **Legal advice:** Provide general legal advice and guidance on a wide range of legal matters, helping users understand their rights and options. Lawyer LLaMA is a powerful tool that can significantly enhance the efficiency and effectiveness of legal research, analysis, and decision-making. It is an invaluable resource for lawyers, paralegals, law students, and anyone else who needs to navigate the complexities of the legal system.

MaxText is a high-performance, highly scalable, open-source LLM written in pure Python/Jax and targeting Google Cloud TPUs and GPUs for training and inference. MaxText achieves high MFUs and scales from single host to very large clusters while staying simple and "optimization-free" thanks to the power of Jax and the XLA compiler. MaxText aims to be a launching off point for ambitious LLM projects both in research and production. We encourage users to start by experimenting with MaxText out of the box and then fork and modify MaxText to meet their needs.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

This repository maintains a list of research papers on LLM-based Multi-Agents, categorized into five main streams: Multi-Agents Framework, Multi-Agents Orchestration and Efficiency, Multi-Agents for Problem Solving, Multi-Agents for World Simulation, and Multi-Agents Datasets and Benchmarks. The repository also includes a survey paper on LLM-based Multi-Agents and a table summarizing the key findings of the survey.

The neo is an open source robotics research platform powered by a OnePlus 3 smartphone and an STM32F205-based CAN interface board, housed in a 3d-printed casing with active cooling. It includes NEOS, a stripped down Android ROM, and offers a modern Linux environment for development. The platform leverages the high performance embedded processor and sensor capabilities of modern smartphones at a low cost. A detailed guide is available for easy construction, requiring online shopping and soldering skills. The total cost for building a neo is approximately $700.

This repository is a collection of papers focused on understanding the internal mechanism of large language models (LLM). It includes research on topics such as how LLMs handle multilingualism, learn in-context, and handle factual associations. The repository aims to provide insights into the inner workings of transformer-based language models through a curated list of papers and surveys.

This repository contains a curated list of resources on generative information retrieval, including research papers, datasets, tools, and applications. Generative information retrieval is a subfield of information retrieval that uses generative models to generate new documents or passages of text that are relevant to a given query. This can be useful for a variety of tasks, such as question answering, summarization, and document generation. The resources in this repository are intended to help researchers and practitioners stay up-to-date on the latest advances in generative information retrieval.

Windows Agent Arena (WAA) is a scalable Windows AI agent platform designed for testing and benchmarking multi-modal, desktop AI agents. It provides researchers and developers with a reproducible and realistic Windows OS environment for AI research, enabling testing of agentic AI workflows across various tasks. WAA supports deploying agents at scale using Azure ML cloud infrastructure, allowing parallel running of multiple agents and delivering quick benchmark results for hundreds of tasks in minutes.

This repository contains a curated list of **papers using Large Language/Multi-Modal Models for Robotics/RL**. Template from awesome-Implicit-NeRF-Robotics Please feel free to send me pull requests or email to add papers! If you find this repository useful, please consider citing and STARing this list. Feel free to share this list with others! ## Overview * Surveys * Reasoning * Planning * Manipulation * Instructions and Navigation * Simulation Frameworks * Citation

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

The IBM Analog Hardware Acceleration Kit is an open-source Python toolkit for exploring and using the capabilities of in-memory computing devices in the context of artificial intelligence. It consists of two main components: Pytorch integration and Analog devices simulator. The Pytorch integration provides a series of primitives and features that allow using the toolkit within PyTorch, including analog neural network modules, analog training using torch training workflow, and analog inference using torch inference workflow. The Analog devices simulator is a high-performant (CUDA-capable) C++ simulator that allows for simulating a wide range of analog devices and crossbar configurations by using abstract functional models of material characteristics with adjustable parameters. Along with the two main components, the toolkit includes other functionalities such as a library of device presets, a module for executing high-level use cases, a utility to automatically convert a downloaded model to its equivalent Analog model, and integration with the AIHW Composer platform. The toolkit is currently in beta and under active development, and users are advised to be mindful of potential issues and keep an eye for improvements, new features, and bug fixes in upcoming versions.

Awesome-Efficient-LLM is a curated list focusing on efficient large language models. It includes topics such as knowledge distillation, network pruning, quantization, inference acceleration, efficient MOE, efficient architecture of LLM, KV cache compression, text compression, low-rank decomposition, hardware/system, tuning, and survey. The repository provides a collection of papers and projects related to improving the efficiency of large language models through various techniques like sparsity, quantization, and compression.

The AI Fairness 360 toolkit is an open-source library designed to detect and mitigate bias in machine learning models. It provides a comprehensive set of metrics, explanations, and algorithms for bias mitigation in various domains such as finance, healthcare, and education. The toolkit supports multiple bias mitigation algorithms and fairness metrics, and is available in both Python and R. Users can leverage the toolkit to ensure fairness in AI applications and contribute to its development for extensibility.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs. It is a systematic & reusable library of 80+ core OPs, 20+ reusable config recipes, and 20+ feature-rich dedicated toolkits, designed to function independently of specific LLM datasets and processing pipelines. Data-Juicer allows detailed data analyses with an automated report generation feature for a deeper understanding of your dataset. Coupled with multi-dimension automatic evaluation capabilities, it supports a timely feedback loop at multiple stages in the LLM development process. Data-Juicer offers tens of pre-built data processing recipes for pre-training, fine-tuning, en, zh, and more scenarios. It provides a speedy data processing pipeline requiring less memory and CPU usage, optimized for maximum productivity. Data-Juicer is flexible & extensible, accommodating most types of data formats and allowing flexible combinations of OPs. It is designed for simplicity, with comprehensive documentation, easy start guides and demo configs, and intuitive configuration with simple adding/removing OPs from existing configs.

Your virtual legal assistant for swift legal research and case management.

A legal research assistant for case discovery.

Legal Insight Analyst-Lia is an advanced AI companion designed to empower legal professionals with unparalleled support in the world of law. By leveraging cutting-edge technologies, Lia simplifies and enhances legal research, analysis, and decision-making processes.

Soy un profesor de derecho digital que busca acercar a los abogados al fascinante mundo de la tecnología.

Upload a court judgment and get back a collection of topical case digests based on the case. Oh - don't trust the "Topic 2210" or similar number, it's random. Also, probably best you not fully trust the output either. We're just playing with the GPT maker. More about us at Jurisage.com.

Simulates legal debates in a text-based GPT game.

Expert in AI legal research by Prof. Kiskinov, SJD

Ekspert za srpsko pravo i sudsku praksu.

En AI-assistent utvecklad av juridikstudenter med expertis inom svensk och EU-lagstiftning för att stödja juridiska yrkesverksamma, studenter och allmänheten.

Expert in Ontario law, offering bilingual legal analysis and practical guidance.

AI immigration law research assistant for case law updates and strategies.