Best AI tools for< Standardize Document Structure >

Everbility is an AI-powered clinical documentation tool designed for Allied Health Professionals. It helps in writing reports, synthesizing client notes, brainstorming ideas, and focusing on client care. The tool saves time by generating progress notes, letters, and assessment reports, while ensuring data privacy and compliance with regulations like HIPAA and Australian Privacy Principles.

Kopyst is an AI-powered documentation tool that revolutionizes the process of creating engaging video and documents. It helps users streamline workflows, create user manuals, SOPs, and training documents with unmatched accuracy and efficiency. Kopyst offers features like instant documentation, versatile application for various document types, AI-powered intelligence, easy sharing and collaboration, and seamless integration with existing tools. The application empowers users to save time, reduce errors, optimize resources, and enhance productivity in documentation tasks.

Dubble is a free tool that helps you create step-by-step guides, tutorials, and onboarding resources for your processes. It uses AI to watch how you work and translate your actions into written instructions and screenshots. This makes it easy to document your processes without having to write anything yourself.

Lawformer is an AI-powered tool designed to simplify the process of handling complex legal documents. It offers an extensive database of attorney-drafted clauses and terms for any contract, along with a learning platform to enhance practical skills in contract drafting. Users can create a personalized library, manage contract knowledge efficiently, and find relevant contract clauses quickly. Lawformer has been serving Silicon Valley startups and the UK's entrepreneurial community since 2009 and 2015, respectively, and is recognized as an international platform for online payments. The platform is trusted by legal professionals and students alike for its comprehensive resources and user-friendly interface.

Enlitic provides healthcare data solutions that leverage artificial intelligence to improve data management, clinical workflows, and create a foundation for real-world evidence medical image databases. Their products, ENDEX and ENCOG, utilize computer vision and natural language processing to standardize, protect, and analyze medical imaging data, enabling healthcare providers to optimize workflows, increase efficiencies, and expand capacity.

Claravine is an AI tool that creates shared language and standards for marketing data. It eliminates flawed data, conflict, and the blame game by ensuring data accuracy, improving accountability, and building trust. The platform helps enterprise brands and agencies deliver on the promise of modern marketing by consistently creating and applying data standards. With features like defining standards, applying standards, and connecting standards, Claravine maximizes campaign and technology investments to drive better results. Customers report significant improvements in return on ad spend, data compliance, and time spent on manual data processes. The platform enables global collaboration, automates data flows, and adapts quickly to changing business needs. Trusted by global brands, Claravine provides visibility into campaign performance, data consistency across organizations, and a single source of truth for marketing data.

Responsible AI Licenses (RAIL) is an initiative that empowers developers to restrict the use of their AI technology to prevent irresponsible and harmful applications. They provide licenses with behavioral-use clauses to control specific use-cases and prevent misuse of AI artifacts. The organization aims to standardize RAIL Licenses, develop collaboration tools, and educate developers on responsible AI practices.

Rafay is an AI-powered platform that accelerates cloud-native and AI/ML initiatives for enterprises. It provides automation for Kubernetes clusters, cloud cost optimization, and AI workbenches as a service. Rafay enables platform teams to focus on innovation by automating self-service cloud infrastructure workflows.

Cercle is an AI platform that advances healthcare for women by transforming healthcare data into real-time, high-quality insights. The platform caters to women's healthcare providers, payors, and pharma companies, helping them run more efficient businesses and provide personalized care. Cercle's Biomedical Graph unlocks insights at unprecedented speed and accuracy, optimizing patient care and improving outcomes in areas such as assisted reproduction and fertility processes.

Klipy is an AI-powered CRM platform that offers a comprehensive solution for managing all aspects of revenue growth. From automating manual tasks to providing insights through AI analytics, Klipy helps businesses streamline their sales processes and enhance customer relationships. The platform is designed to enrich, log, and organize deal flows, while also offering features like call analytics, playbooks, and pipeline orchestration. Klipy is trusted by various companies and is known for its security measures, ensuring data protection through encryption and anonymization. With a focus on growth operations management, Klipy aims to simplify the sales enablement process and improve customer loyalty.

Laudio is an intelligent platform designed to help frontline leaders in health systems streamline their work and prioritize high-impact actions with their teams. By integrating essential workflows and leveraging AI technology, Laudio aims to drive large-scale change by saving time, standardizing best practices, and improving employee engagement and patient experience.

Vidya.us is an AI-powered platform designed to enhance student engagement by generating thought-provoking and customized questions for effective collaboration in educational settings. The platform offers an AI question generator to simplify classroom engagement, unlimited question libraries for collaboration, and live classroom parameter measurement. Vidya.us aims to streamline content creation and delivery in schools, colleges, and workplaces through innovative AI technology.

Ongig is an AI-powered software that focuses on enhancing job postings for consistency, inclusivity, and efficiency. It offers solutions to common problems in job descriptions such as manual workflows, inconsistent postings, and bias. Ongig's features include a centralized job library, AI for talent acquisition, ATS integration, HRIS automation, and job description API. The application helps standardize job ads, improve readability, build a job library, remove gender-coded language, and provide API-driven insights for smarter hiring decisions.

Tabula is a visual data analytics tool that uses AI to help businesses get insights from their data. It is easy to use and can be used by anyone, regardless of their technical expertise. Tabula can be used to access and unify data from a variety of sources, standardize and blend datasets, add custom metrics, build stunning reports, and automate repetitive tasks. Tabula is integrated with a variety of data sources and platforms, making it easy to get started.

AudioShake is a cloud-based audio processing platform that uses artificial intelligence (AI) to separate audio into its component parts, such as vocals, music, and effects. This technology can be used for a variety of applications, including mixing and mastering, localization and captioning, interactive audio, and sync licensing.

Apiversion.dev is an AI-powered API versioning platform that helps developers manage and version their APIs. It provides a range of features to make API versioning easier, including automatic versioning, version deprecation, and version promotion. Apiversion.dev also integrates with popular CI/CD tools to automate the API versioning process.

The Princeton Review is an AI-based test preparation and tutoring platform offering personalized academic support, test prep courses, and college admissions counseling. With over 43 years of industry experience and a track record of helping millions of students, The Princeton Review uses sophisticated AI technology to provide students with tailored learning experiences, expert-led videos, interactive reports, and feedback tools for essays and homework. The platform covers a wide range of subjects and exams, from K-12 academics to graduate and professional tests like SAT, ACT, MCAT, LSAT, GRE, GMAT, and more. Additionally, it offers services for college admissions counseling, school partnerships, and international licensing.

ReadTheory is a free online reading comprehension practice tool for students and teachers. It offers personalized reading comprehension exercises for grades K-12 and ESL students, with adaptive technology that adjusts to each student's specific reading level. ReadTheory also provides teachers with easy-to-use reporting and thousands of interactive exercises and worksheets. With ReadTheory, teachers can save time with automatic marking, track individual student and class progress in real-time, and motivate students to read with engaging class competitions, badges, and prizes.

Vervoe is an AI-powered recruitment platform and hiring solution that revolutionizes the hiring process by offering skills-based screening through AI job simulations and assessments. It streamlines interviews, provides standardized templates, and facilitates team collaboration. Vervoe enables data-backed decisions by ranking applicants based on performance and offering detailed reports. The platform focuses on task-based evaluations of job-specific skills, enhancing the accuracy of hiring decisions. Employers can create customized tests or choose from a library of scientifically mapped assessments. Vervoe uses AI for recruiting, grading, and ranking candidates efficiently. The platform enhances employer branding, offers candidate feedback, and ensures a seamless candidate experience. Vervoe caters to various industries and company types, making it a versatile tool for modern recruitment processes.

Clearbit is a B2B marketing intelligence platform that provides data enrichment, scoring, routing, and buying intent signals. It is powered by artificial intelligence and is the first HubSpot Native Data Provider. Clearbit's data foundation is built on public data from the web, proprietary data, and the power of LLMs to convert unstructured information into precise and standardized data sets. This data can be used to enrich leads, contacts, and accounts, and to identify hidden buying intent. Clearbit also offers a variety of features to help businesses score and route leads, and to create better converting forms.

The Codebase Context Specification (CCS) project aims to standardize embedding contextual information within codebases to enhance understanding for both AI and human developers. It introduces a convention similar to `.env` and `.editorconfig` files but focused on documenting code for both AI and humans. By providing structured contextual metadata, collaborative documentation guidelines, and standardized context files, developers can improve code comprehension, collaboration, and development efficiency. The project includes a linter for validating context files and provides guidelines for using the specification with AI assistants. Tooling recommendations suggest creating memory systems, IDE plugins, AI model integrations, and agents for context creation and utilization. Future directions include integration with existing documentation systems, dynamic context generation, and support for explicit context overriding.

This repository serves as a comprehensive survey on the application of Large Language Models (LLMs) on tabular data, focusing on tasks such as prediction, data generation, and table understanding. It aims to consolidate recent progress in this field by summarizing key techniques, metrics, datasets, models, and optimization approaches. The survey identifies strengths, limitations, unexplored territories, and gaps in the existing literature, providing insights for future research directions. It also offers code and dataset references to empower readers with the necessary tools and knowledge to address challenges in this rapidly evolving domain.

AiDE is a lightweight framework for structuring AI-assisted development. It standardizes project context management, documentation, and collaboration, ensuring the assistant stays informed and productive throughout the project lifecycle. It offers drop-in simplicity with no dependencies, versatile usage for new and existing projects, and standardized templates for roadmaps, tasks, decisions, and sessions. The framework helps track project state, decision records, task management, and session tracking. It encourages best practices like starting each session by reviewing `.context` files, tracking task completion, documenting key decisions, and recording session summaries. The folder structure includes files for current state, roadmap, tasks, decisions, and sessions, with specific directories for active, completed, hold, and planned tasks. Contributions are welcome to enhance the usability of `.context`, and optional global rules for AI assistants are provided to optimize integration with the framework.

OpenKF (Open Knowledge Flow) is an online intelligent customer service system. It is an open-source customer service system based on OpenIM, supporting LLM (Local Knowledgebase) customer service and multi-channel customer service. It is easy to integrate with third-party systems, deploy, and perform secondary development. The system provides features like login page, config page, dashboard page, platform page, and session page. Users can quickly get started with OpenKF by following the installation and run instructions. The architecture follows MVC design with a standardized directory structure. The community encourages involvement through community meetings, contributions, and development. OpenKF is licensed under the Apache 2.0 license.

tinyllm is a lightweight framework designed for developing, debugging, and monitoring LLM and Agent powered applications at scale. It aims to simplify code while enabling users to create complex agents or LLM workflows in production. The core classes, Function and FunctionStream, standardize and control LLM, ToolStore, and relevant calls for scalable production use. It offers structured handling of function execution, including input/output validation, error handling, evaluation, and more, all while maintaining code readability. Users can create chains with prompts, LLM models, and evaluators in a single file without the need for extensive class definitions or spaghetti code. Additionally, tinyllm integrates with various libraries like Langfuse and provides tools for prompt engineering, observability, logging, and finite state machine design.

Awesome MCP Servers is a curated list of Model Context Protocol (MCP) servers that enable AI models to securely interact with local and remote resources through standardized server implementations. The list includes production-ready and experimental servers that extend AI capabilities through file access, database connections, API integrations, and other contextual services.

ATLAS (Adaptive Task & Logic Automation System) is a high-performance Model Context Protocol server designed for LLMs to manage complex task hierarchies. Built with TypeScript, it features ACID-compliant storage, efficient task tracking, and intelligent template management. ATLAS provides LLM Agents task management through a clean, flexible tool interface. The server implements the Model Context Protocol (MCP) for standardized communication between LLMs and external systems, offering hierarchical task organization, task state management, smart templates, enterprise features, and performance optimization.

The AI Enablement Stack is a curated collection of venture-backed companies, tools, and technologies that enable developers to build, deploy, and manage AI applications. It provides a structured view of the AI development ecosystem across five key layers: Agent Consumer Layer, Observability and Governance Layer, Engineering Layer, Intelligence Layer, and Infrastructure Layer. Each layer focuses on specific aspects of AI development, from end-user interaction to model training and deployment. The stack aims to help developers find the right tools for building AI applications faster and more efficiently, assist engineering leaders in making informed decisions about AI infrastructure and tooling, and help organizations understand the AI development landscape to plan technology adoption.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

OpenAdapt is an open-source software adapter between Large Multimodal Models (LMMs) and traditional desktop and web Graphical User Interfaces (GUIs). It aims to automate repetitive GUI workflows by leveraging the power of LMMs. OpenAdapt records user input and screenshots, converts them into tokenized format, and generates synthetic input via transformer model completions. It also analyzes recordings to generate task trees and replay synthetic input to complete tasks. OpenAdapt is model agnostic and generates prompts automatically by learning from human demonstration, ensuring that agents are grounded in existing processes and mitigating hallucinations. It works with all types of desktop GUIs, including virtualized and web, and is open source under the MIT license.

Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.

LongBench v2 is a benchmark designed to assess the ability of large language models (LLMs) to handle long-context problems requiring deep understanding and reasoning across various real-world multitasks. It consists of 503 challenging multiple-choice questions with contexts ranging from 8k to 2M words, covering six major task categories. The dataset is collected from nearly 100 highly educated individuals with diverse professional backgrounds and is designed to be challenging even for human experts. The evaluation results highlight the importance of enhanced reasoning ability and scaling inference-time compute to tackle the long-context challenges in LongBench v2.

Awesome Khmer Language is a comprehensive collection of resources for the Khmer language, including tools, datasets, research papers, projects/models, blogs/slides, and miscellaneous items. It covers a wide range of topics related to Khmer language processing, such as character normalization, word segmentation, part-of-speech tagging, optical character recognition, text-to-speech, and more. The repository aims to support the development of natural language processing applications for the Khmer language by providing a diverse set of resources and tools for researchers and developers.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

Eden AI aims to simplify the use and deployment of AI technologies by providing a unique API that connects to all the best AI engines. With the rise of **AI as a Service** , a lot of companies provide off-the-shelf trained models that you can access directly through an API. These companies are either the tech giants (Google, Microsoft , Amazon) or other smaller, more specialized companies, and there are hundreds of them. Some of the most known are : DeepL (translation), OpenAI (text and image analysis), AssemblyAI (speech analysis). There are **hundreds of companies** doing that. We're regrouping the best ones **in one place** !

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