Best AI tools for< Analyze Structured Data >

Dataku.ai is an advanced data extraction and analysis tool powered by AI technology. It offers seamless extraction of valuable insights from documents and texts, transforming unstructured data into structured, actionable information. The tool provides tailored data extraction solutions for various needs, such as resume extraction for streamlined recruitment processes, review insights for decoding customer sentiments, and leveraging customer data to personalize experiences. With features like market trend analysis and financial document analysis, Dataku.ai empowers users to make strategic decisions based on accurate data. The tool ensures precision, efficiency, and scalability in data processing, offering different pricing plans to cater to different user needs.

Isomeric is an AI tool that uses artificial intelligence to semantically understand unstructured text and extract specific data. It transforms messy text into machine-readable JSON, enabling users to scale their data gathering pipeline in seconds. From web scraping to browser extensions to general information extraction, Isomeric offers a solution to bring order to chaos and make unstructured data structured and usable.

NuMind is an AI tool designed to solve information extraction tasks efficiently. It offers high-quality lightweight models tailored to users' needs, automating classification, entity recognition, and structured extraction. The tool is powered by task-specific and domain-agnostic foundation models, outperforming GPT-4 and similar models. NuMind provides solutions for various industries such as insurance and healthcare, ensuring privacy, cost-effectiveness, and faster NLP projects.

unSurvey is an AI tool that allows users to create personalized conversational agents for gathering and analyzing information at scale. It helps in saving time by converting conversations into deep insights and structured data within minutes. The tool is designed to assist in creating Privacy Policy and conducting surveys efficiently.

Receipt OCR API by ReceiptUp is an advanced tool that leverages OCR and AI technology to extract structured data from receipt and invoice images. The API offers high accuracy and multilingual support, making it ideal for businesses worldwide to streamline financial operations. With features like multilingual support, high accuracy, support for multiple formats, accounting downloads, and affordability, Receipt OCR API is a powerful tool for efficient receipt management and data extraction.

TextMine is an AI-powered knowledge base designed for businesses to manage and analyze critical documents efficiently. It offers features such as document analysis, smart-search capabilities, automated data extraction, and structured dataset transformation. TextMine helps businesses save time and money by streamlining document management processes and enabling informed decision-making. The application caters to various industries like Technology, Legal Services, and Financial Services, providing solutions for teams in Procurement, Finance, Compliance, CIOs, and CDOs.

Beatandraise is an AI-powered Equity Research tool that combines AI and ChatGPT technology to provide users with a comprehensive platform for analyzing SEC filings. Users can chat with every SEC filing, access all SEC filings since 1995, find related documents easily, leverage AI search capabilities, download tables to Excel, and collaborate with integrated note-taking features. The platform aims to streamline the equity research process by offering a centralized hub for accessing and analyzing financial information.

Pipeless Agents is a platform that allows users to convert any video feed into an actionable data stream, enabling automation of tasks based on visual inputs. It serves as a serverless platform for Vision AI, offering the ability to create projects, connect video sources, and customize agents for specific needs. With a focus on simplicity and efficiency, Pipeless Agents empowers users to extract structured data from various video sources and automate processes with minimal coding requirements.

ResuMetrics is an AI-powered platform designed to streamline the resume processing workflow. It offers solutions to extract structured data from resumes and automate the anonymization process. The platform provides an easy-to-use API for automating resume analysis, including candidate onboarding and PII redaction. With features like resume scoring and vacancy matching on the roadmap, ResuMetrics aims to enhance the efficiency of resume processing tasks. Users can choose from different subscription plans based on their processing needs, with credits consumed per document page. Overall, ResuMetrics is a comprehensive tool for organizations looking to optimize their resume processing operations.

Wikidata is a free and open knowledge base that can be read and edited by both humans and machines. It acts as central storage for the structured data of its Wikimedia sister projects including Wikipedia, Wikivoyage, Wiktionary, Wikisource, and others. Wikidata also provides support to many other sites and services beyond just Wikimedia projects!

Talking Tree is an AI-powered document management tool designed for legal professionals to digitize and manage legal documents efficiently. It offers advanced OCR technology and a custom RAG architecture to convert printed and handwritten text into searchable structured data. The platform enables users to find information, draft agreements, and analyze legacy documents with unprecedented speed and accuracy. Talking Tree provides a secure and user-friendly interface with multilingual support, making it a valuable resource for legal research and document management.

Doc2cart is an AI-powered platform that automates the extraction of product information from various documents such as invoices, price lists, and catalogs. It utilizes advanced OCR technology to convert paper or digital documents into structured e-commerce data that can be seamlessly integrated into popular e-commerce platforms and shopping carts. The platform focuses on data extraction and processing, providing users with the flexibility to utilize the extracted data in their systems efficiently.

TalkForm AI is an AI-powered form creation and filling tool that revolutionizes the traditional form-building process. With the ability to chat to create and chat to fill forms, TalkForm AI offers a seamless and efficient solution for creating and managing forms. The application leverages AI technology to automatically infer field types, validate, clean, structure, and fill form responses, ensuring data remains structured for easy analysis. TalkForm AI also provides custom validations, complicated conditional logic, and unlimited power to cater to diverse form creation needs.

Docugami is an AI-powered document engineering platform that enables business users to extract, analyze, and automate data from various types of documents. It empowers users with immediate impact without the need for extensive machine learning investments or IT development. Docugami's proprietary Business Document Foundation Model leverages Generative AI to transform unstructured text into structured information, allowing users to unlock insights and drive business processes efficiently.

Quantexa News API is an AI-powered news data application that provides efficient, effective, and accurate access to global news at scale. It offers real-time access to enriched, tagged, and structured news feeds, enhancing risk monitoring processes and models. The application aggregates news content from over 90,000 sources and 1.3 million NLP-enriched news articles daily, with advanced AI-powered search capabilities. Users can investigate data through visualizations, automate tasks with entity and sentiment analysis, and easily share news data with relevant stakeholders.

Docugami is an AI-powered document engineering platform that enables business users to extract, analyze, and automate data from various types of documents. It empowers users with immediate impact without the need for extensive machine learning investments or IT development. Docugami's proprietary Business Document Foundation Model and Generative AI technology transform unstructured text and tables into structured information, allowing users to unlock insights, increase productivity, and ensure compliance.

Censius is an AI Observability Platform for Enterprise ML Teams. It provides end-to-end visibility of structured and unstructured production models, enabling proactive model management and continuous delivery of reliable ML. Key features include model monitoring, explainability, and analytics.

Co-Founder AI is an AI-powered tool that accelerates startup success by providing in-depth business reports and actionable insights. It utilizes AI to generate well-structured business plans and offers essential insights to validate IT-business ideas. The tool covers various aspects such as market trends, competitor analysis, sales techniques, and fundraising strategies, enabling users to make data-driven decisions for driving growth.

The website is an AI tool designed to generate a knowledge graph based on input text. It uses advanced algorithms and machine learning capabilities to streamline operations, deliver personalized experiences, and unlock new possibilities. Users can input text related to various topics, and the tool processes the information to create a structured knowledge graph.

LiveSnap is an AI-powered strategic intelligence platform that enables users to find, analyze, and monitor relevant information from billions of sources. It centralizes essential information, automates data collection, provides real-time monitoring of conversations, and offers intelligent summaries for quick insights. The platform also facilitates automated report generation, historical data tracking, and categorization of information for efficient decision-making. LiveSnap leverages artificial intelligence to save time on repetitive tasks, ensuring users focus on critical activities. By using LiveSnap, organizations benefit from filtered and structured information, centralized data access, and automated preliminary analysis, leading to informed decision-making and time savings.

Phoenix is a tool that provides MLOps and LLMOps insights at lightning speed with zero-config observability. It offers a notebook-first experience for monitoring models and LLM Applications by providing LLM Traces, LLM Evals, Embedding Analysis, RAG Analysis, and Structured Data Analysis. Users can trace through the execution of LLM Applications, evaluate generative models, explore embedding point-clouds, visualize generative application's search and retrieval process, and statistically analyze structured data. Phoenix is designed to help users troubleshoot problems related to retrieval, tool execution, relevance, toxicity, drift, and performance degradation.

EDA GPT is an open-source data analysis companion that offers a comprehensive solution for structured and unstructured data analysis. It streamlines the data analysis process, empowering users to explore, visualize, and gain insights from their data. EDA GPT supports analyzing structured data in various formats like CSV, XLSX, and SQLite, generating graphs, and conducting in-depth analysis of unstructured data such as PDFs and images. It provides a user-friendly interface, powerful features, and capabilities like comparing performance with other tools, analyzing large language models, multimodal search, data cleaning, and editing. The tool is optimized for maximal parallel processing, searching internet and documents, and creating analysis reports from structured and unstructured data.

ERAG is an advanced system that combines lexical, semantic, text, and knowledge graph searches with conversation context to provide accurate and contextually relevant responses. This tool processes various document types, creates embeddings, builds knowledge graphs, and uses this information to answer user queries intelligently. It includes modules for interacting with web content, GitHub repositories, and performing exploratory data analysis using various language models.

This Python library enhances OpenAI chat completion responses by providing detailed information about token log probabilities. It works with OpenAI Structured Outputs to ensure model-generated responses adhere to a JSON Schema. Developers can analyze and incorporate token-level log probabilities to understand the reliability of structured data extracted from OpenAI models.

GenAIScript is a scripting environment designed to facilitate file ingestion, prompt development, and structured data extraction. Users can define metadata and model configurations, specify data sources, and define tasks to extract specific information. The tool provides a convenient way to analyze files and extract desired content in a structured format. It offers a user-friendly interface for working with data and automating data extraction processes, making it suitable for various data processing tasks.

This repository contains a collection of code samples that demonstrate how to use various Azure AI capabilities to process documents. The samples help engineering teams establish techniques with Azure AI Foundry, Azure OpenAI, Azure AI Document Intelligence, and Azure AI Language services to build solutions for extracting structured data, classifying, and analyzing documents. The techniques simplify custom model training, improve reliability in document processing, and simplify document processing workflows by providing reusable code and patterns that can be easily modified and evaluated for most use cases.

Instructor for PHP is a library designed for structured data extraction in PHP, powered by Large Language Models (LLMs). It simplifies the process of extracting structured, validated data from unstructured text or chat sequences. Instructor enhances workflow by providing a response model, validation capabilities, and max retries for requests. It supports classes as response models and provides features like partial results, string input, extracting scalar and enum values, and specifying data models using PHP type hints or DocBlock comments. The library allows customization of validation and provides detailed event notifications during request processing. Instructor is compatible with PHP 8.2+ and leverages PHP reflection, Symfony components, and SaloonPHP for communication with LLM API providers.

ProLLM is a framework that leverages Large Language Models to interpret and analyze protein sequences and interactions through natural language processing. It introduces the Protein Chain of Thought (ProCoT) method to transform complex protein interaction data into intuitive prompts, enhancing predictive accuracy by incorporating protein-specific embeddings and fine-tuning on domain-specific datasets.

gollm is a Go package designed to simplify interactions with Large Language Models (LLMs) for AI engineers and developers. It offers a unified API for multiple LLM providers, easy provider and model switching, flexible configuration options, advanced prompt engineering, prompt optimization, memory retention, structured output and validation, provider comparison tools, high-level AI functions, robust error handling and retries, and extensible architecture. The package enables users to create AI-powered golems for tasks like content creation workflows, complex reasoning tasks, structured data generation, model performance analysis, prompt optimization, and creating a mixture of agents.

Extractor is an AI-powered data extraction library for Laravel that leverages OpenAI's capabilities to effortlessly extract structured data from various sources, including images, PDFs, and emails. It features a convenient wrapper around OpenAI Chat and Completion endpoints, supports multiple input formats, includes a flexible Field Extractor for arbitrary data extraction, and integrates with Textract for OCR functionality. Extractor utilizes JSON Mode from the latest GPT-3.5 and GPT-4 models, providing accurate and efficient data extraction.

Simplemind is an AI library designed to simplify the experience with AI APIs in Python. It provides easy-to-use AI tools with a human-centered design and minimal configuration. Users can tap into powerful AI capabilities through simple interfaces, without needing to be experts. The library supports various APIs from different providers/models and offers features like text completion, streaming text, structured data handling, conversational AI, tool calling, and logging. Simplemind aims to make AI models accessible to all by abstracting away complexity and prioritizing readability and usability.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

This repository contains samples to help design AI applications using data from an Azure SQL Database. It showcases technical concepts and workflows integrating Azure SQL data with popular AI components both within and outside Azure. The samples cover various AI features such as Azure Cognitive Services, Promptflow, OpenAI, Vanna.AI, Content Moderation, LangChain, and more. Additionally, there are end-to-end samples like Similar Content Finder, Session Conference Assistant, Chatbots, Vectorization, SQL Server Database Development, Redis Vector Search, and Similarity Search with FAISS.

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.

PyLLMCore is a light-weighted interface with Large Language Models with native support for llama.cpp, OpenAI API, and Azure deployments. It offers a Pythonic API that is simple to use, with structures provided by the standard library dataclasses module. The high-level API includes the assistants module for easy swapping between models. PyLLMCore supports various models including those compatible with llama.cpp, OpenAI, and Azure APIs. It covers use cases such as parsing, summarizing, question answering, hallucinations reduction, context size management, and tokenizing. The tool allows users to interact with language models for tasks like parsing text, summarizing content, answering questions, reducing hallucinations, managing context size, and tokenizing text.

Resume Job Matcher is a Python script that automates the process of matching resumes to a job description using AI. It leverages the Anthropic Claude API or OpenAI's GPT API to analyze resumes and provide a match score along with personalized email responses for candidates. The tool offers comprehensive resume processing, advanced AI-powered analysis, in-depth evaluation & scoring, comprehensive analytics & reporting, enhanced candidate profiling, and robust system management. Users can customize font presets, generate PDF versions of unified resumes, adjust logging level, change scoring model, modify AI provider, and adjust AI model. The final score for each resume is calculated based on AI-generated match score and resume quality score, ensuring content relevance and presentation quality are considered. Troubleshooting tips, best practices, contribution guidelines, and required Python packages are provided.

Crawl4AI is a powerful and free web crawling service that extracts valuable data from websites and provides LLM-friendly output formats. It supports crawling multiple URLs simultaneously, replaces media tags with ALT, and is completely free to use and open-source. Users can integrate Crawl4AI into Python projects as a library or run it as a standalone local server. The tool allows users to crawl and extract data from specified URLs using different providers and models, with options to include raw HTML content, force fresh crawls, and extract meaningful text blocks. Configuration settings can be adjusted in the `crawler/config.py` file to customize providers, API keys, chunk processing, and word thresholds. Contributions to Crawl4AI are welcome from the open-source community to enhance its value for AI enthusiasts and developers.

This repository contains examples, applications, starter code, & tutorials to help you kickstart your GenAI projects. * These are built using LanceDB, a free, open-source, serverless vectorDB that **requires no setup**. * It **integrates into python data ecosystem** so you can simply start using these in your existing data pipelines in pandas, arrow, pydantic etc. * LanceDB has **native Typescript SDK** using which you can **run vector search** in serverless functions! This repository is divided into 3 sections: - Examples - Get right into the code with minimal introduction, aimed at getting you from an idea to PoC within minutes! - Applications - Ready to use Python and web apps using applied LLMs, VectorDB and GenAI tools - Tutorials - A curated list of tutorials, blogs, Colabs and courses to get you started with GenAI in greater depth.

MyScaleDB is a SQL vector database designed for scalable AI applications, enabling developers to efficiently manage and process massive volumes of data using familiar SQL. It offers fast and efficient vector search, filtered search, and SQL-vector join queries. MyScaleDB is fully SQL-compatible and production-ready for AI applications, providing unmatched performance and scalability through cutting-edge OLAP architecture and advanced vector algorithms. Built on top of ClickHouse, it combines structured and vectorized data management for high accuracy and speed in filtered searches.

Structured analyzer of business case PDFs with tailored insights.

Structured financial analysis with investment advisory and simulations.

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Analyzes email headers for security insights, presenting data in a structured table view.

Psychology data analysis expert that guides users through structured, step-by-step exploration of a CSV data set. The analysis is based on research questions.

I provide monthly salary data in euros, using a structured format for global job roles.

In-depth CIM analysis with a structured rating scale, offering detailed business evaluations.

Generate a Structured description in typescript format from the image and generate an image from that description.　and OCR

Interactive ML/AI tutor providing structured daily lessons.

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I provide a structured way of using AI to support teaching and learning. I use the the CHOICE method (i.e., Clarify, Harness, Originate, Iterate, Communicate, Evaluate) to ensure that your use of AI can help you meet your educational goals.

Debunks misinformation with structured, evidence-based responses and citations.

Let me help you expand your online presence, attract new customers, and retain them effectively. Here's a structured approach we can take based on the RACE (Reach, Act, Convert, Engage) framework

A gpt assistant that helps with analyzing a startup/market. The answers you get back is already structured to give you the core elements you would want to see in an investment memo/ market analysis

Extracts and structures web content in formal, technical language.

I analyze and integrate missing clusters in data for coherent structuring.

Guides data structure design with tailored, step-by-step insights.