Best AI tools for< Research Financial Data >

Finlo is an AI-powered financial research assistant that provides comprehensive market insights, financial data, and analysis tools for investors. It simplifies complex financial information into understandable insights, offering real-time monitoring, trend analysis, comparative insights, and personalized recommendations to help users make informed investment decisions. With knowledge of earnings releases, financial reports, and fundamental information for S&P 500 and Nasdaq companies, Finlo aims to enhance decision-making and confidence in navigating the stock market.

FinChat.io is a comprehensive AI-powered stock research platform that provides institutional-quality data and insights to investors. With FinChat.io, you can access accurate financial data on over 100,000 global public companies, as well as company revenue and profit segments, KPIs, analyst estimates, price targets, and ratings. FinChat.io also utilizes cutting-edge AI to build summaries, models, and visualizations, making it easy to understand complex financial data. Additionally, FinChat.io offers a customizable terminal, allowing you to track what matters most to you and auto-save your research. With FinChat.io, you can work faster than ever and make better investment decisions.

Daloopa is an AI financial modeling tool designed to automate fundamental data updates for financial analysts working in Excel. It helps analysts build and update financial models efficiently by eliminating manual work and providing accurate, auditable data points sourced from thousands of companies. Daloopa leverages AI technology to deliver complete and comprehensive data sets faster than humanly possible, enabling analysts to focus on analysis, insight generation, and idea development to drive better investment decisions.

Reportify is an AI platform for investment research that provides detailed analysis and insights on various companies, filings, transcripts, reports, and news. Users can explore financial data, performance metrics, and market trends to make informed investment decisions. The platform offers a comprehensive view of the investment landscape, including company histories, financial reports, and industry analysis.

CityFALCON is a financial and business due diligence platform that provides a range of solutions for the needs of a wide audience, including retail investors, retail traders, daily business news readers, brokers, students, professors, academia, wealth managers, financial advisors, P2P crowdfunding, VC, PE, institutional investors, treasury, consultancy, legal, accounting, central banks, and regulatory agencies. The platform offers a variety of features and content, including a CityFALCON Score, watchlists, similar stories, grouping news on charts, key headlines, sentiment content translation, content news premium publications, insider transactions, official company filings, investor relations, ESG content, and languages.

PrometAI is an AI-powered business plan generator that helps entrepreneurs and businesses create comprehensive and professional business plans. It offers a range of features and tools to guide users through each step of the planning process, including strategy development, financial analysis, and valuation. PrometAI's platform is designed to simplify and streamline the business planning process, making it accessible to users of all levels of experience.

Monexa is a professional-grade financial analysis platform that offers institutional-grade market insights, news, and data analysis in one powerful platform. It provides comprehensive market analysis, AI-powered insights, rich data visualizations, research and analysis tools, advanced screener, rich financial history, automated SWOT analysis, comprehensive reports, interactive performance analytics, institutional investment tracking, company intelligence, dividend analysis, earnings call analysis, portfolio analytics, strategy explorer, real-time market intelligence, and more. Monexa is designed to help users make data-driven investment decisions with a comprehensive suite of analytical capabilities.

Thomson Reuters is a leading provider of business information services. The company provides a wide range of products and services to professionals in the legal, tax, accounting, and risk management industries. Thomson Reuters' products and services include news and information, research and analysis, software and technology, and education and training. The company has a global presence with operations in over 100 countries.

Decode Investing is an AI tool designed to help users discover and analyze businesses for investment purposes. The platform offers a range of features such as an AI Chat assistant, stock screener, and analysis of SEC filings and earnings calls. Users can access a leaderboard to track performance and insights on various projects. Decode Investing is a comprehensive tool that aims to simplify the investment process by providing valuable data and insights to users.

Stock Market GPT is an AI-powered investment research tool that provides investors with in-depth analysis and insights into global equities. It uses advanced AI models, including GPT-4, to help investors make better investment decisions. The tool offers a range of features, including stock comparison, live data, and growth-focused pricing.

Stockpulse is an AI-powered platform that analyzes financial news and communities using Artificial Intelligence. It provides decision support for operations by collecting, filtering, and converting unstructured data into processable information. With extensive coverage of financial media sources globally, Stockpulse offers unique historical data, sentiment analysis, and AI-driven insights for various sectors in the financial markets.

Kavout is an AI-powered financial research assistant that provides investors with data-driven insights and cutting-edge technology to help them make informed investment decisions. The platform offers a range of features, including natural language search, stock screening, portfolio analysis, and personalized recommendations. Kavout's AI algorithms adapt to each user's unique investment style, providing tailored insights and guidance.

StockGPT is an AI-powered financial research assistant that provides knowledge of earnings releases, financial reports, and fundamental information for S&P 500 and Nasdaq companies. It offers features like AI search, customizable filters, industry research, and up-to-date data to help users analyze companies and markets more efficiently.

AI Just Works is an AI-powered platform that showcases a variety of AI applications across different domains such as financial research, job search, creative tools, game, credit card management, text analytics, product development, sales demos, screen time management, data integration, trip planning, education, health & fitness, movie discovery, AI collaboration, and more. The platform serves as a hub for users to explore and discover innovative AI tools to enhance productivity and efficiency in various tasks and industries.

The AI in Finance Summit is a leading conference that brings together experts in artificial intelligence and finance to discuss the latest trends and developments in the field. The summit features a variety of speakers, including researchers, practitioners, and investors, who share their insights on how AI is being used to transform the financial industry. The summit also provides a platform for attendees to network and learn from each other.

Meyka is an AI-powered stock research tool that provides users with real-time stock data and analysis. Users can explore financial health, social sentiment analysis, earnings reports, comparison of financial statements, stock market news, DCF value, stock price forecasting, and recent grades for various stocks. The tool aims to assist users in making informed investment decisions by leveraging AI technology to analyze and predict stock market trends.

DataSpark AI Multi-Agent Platform is an advanced artificial intelligence tool developed by DataSpark, Inc. The platform leverages cutting-edge AI technology to provide users with a powerful solution for multi-agent systems. With DataSpark AI, users can access the first GenAI Super Agent, enabling them to discover new insights and make informed decisions. The platform is designed to streamline complex processes and enhance productivity across various industries.

dataset.macgence is an AI-powered data analysis tool that helps users extract valuable insights from their datasets. It offers a user-friendly interface for uploading, cleaning, and analyzing data, making it suitable for both beginners and experienced data analysts. With advanced algorithms and visualization capabilities, dataset.macgence enables users to uncover patterns, trends, and correlations in their data, leading to informed decision-making. Whether you're a business professional, researcher, or student, dataset.macgence can streamline your data analysis process and enhance your data-driven strategies.

AnalyStock.ai is a financial application leveraging AI to provide users with a next-generation investment toolbox. It helps users better understand businesses, risks, and make informed investment decisions. The platform offers direct access to the stock market, powerful data-driven tools to build top-ranking portfolios, and insights into company valuations and growth prospects. AnalyStock.ai aims to optimize the investment process, offering a reliable strategy with factors like A-Score, factor investing scores for value, growth, quality, volatility, momentum, and yield. Users can discover hidden gems, fine-tune filters, access company scorecards, perform activity analysis, understand industry dynamics, evaluate capital structure, profitability, and peers' valuation. The application also provides adjustable DCF valuation, portfolio management tools, net asset value computation, monthly commentary, and an AI assistant for personalized insights and assistance.

Super AI is a generative AI tool designed as a copilot for data analysts. It is trained by top-tier product company experts and domain experts to provide unparalleled expertise in research, visualization, and data delivery. The tool goes beyond data processing by generating a comprehensive Business Decision Canvas tailored to specific challenges. Super AI offers guided insights, data modeling suggestions, and effortless integration with legacy BI systems. It is designed to convert business requirements into concrete objectives and is supported by a team of domain experts to mentor the AI. With applications in various industries, Super AI accelerates the process of finding business KPIs and generating data stories with expert intelligence.

Financial Datasets is an open-source Python library that allows users to create question and answer financial datasets using Large Language Models (LLMs). With this library, users can easily generate realistic financial datasets from 10-K, 10-Q, PDF, and other financial texts. The library provides three main methods for generating datasets: from any text, from a 10-K filing, or from a PDF URL. Financial Datasets can be used for a variety of tasks, including financial analysis, research, and education.

AI Financial Agent is a proof of concept project exploring the use of AI for investment research. It provides an AI SDK with a unified API for generating text and structured objects, along with access to real-time and historical stock market data optimized for AI financial agents. The project includes features like dynamic chat interfaces, support for multiple model providers, and styling with Tailwind CSS. Users can deploy their own version of the AI Financial Agent using Vercel and GitHub integration.

PIXIU is a project designed to support the development, fine-tuning, and evaluation of Large Language Models (LLMs) in the financial domain. It includes components like FinBen, a Financial Language Understanding and Prediction Evaluation Benchmark, FIT, a Financial Instruction Dataset, and FinMA, a Financial Large Language Model. The project provides open resources, multi-task and multi-modal financial data, and diverse financial tasks for training and evaluation. It aims to encourage open research and transparency in the financial NLP field.

The `sec-parser` project simplifies extracting meaningful information from SEC EDGAR HTML documents by organizing them into semantic elements and a tree structure. It helps in parsing SEC filings for financial and regulatory analysis, analytics and data science, AI and machine learning, causal AI, and large language models. The tool is especially beneficial for AI, ML, and LLM applications by streamlining data pre-processing and feature extraction.

FinRobot is an open-source AI agent platform designed for financial applications using large language models. It transcends the scope of FinGPT, offering a comprehensive solution that integrates a diverse array of AI technologies. The platform's versatility and adaptability cater to the multifaceted needs of the financial industry. FinRobot's ecosystem is organized into four layers, including Financial AI Agents Layer, Financial LLMs Algorithms Layer, LLMOps and DataOps Layers, and Multi-source LLM Foundation Models Layer. The platform's agent workflow involves Perception, Brain, and Action modules to capture, process, and execute financial data and insights. The Smart Scheduler optimizes model diversity and selection for tasks, managed by components like Director Agent, Agent Registration, Agent Adaptor, and Task Manager. The tool provides a structured file organization with subfolders for agents, data sources, and functional modules, along with installation instructions and hands-on tutorials.

Qlib is an open-source, AI-oriented quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It covers the entire chain of quantitative investment, from alpha seeking to order execution. The platform empowers researchers to explore ideas and implement productions using AI technologies in quantitative investment. Qlib collaboratively solves key challenges in quantitative investment by releasing state-of-the-art research works in various paradigms. It provides a full ML pipeline for data processing, model training, and back-testing, enabling users to perform tasks such as forecasting market patterns, adapting to market dynamics, and modeling continuous investment decisions.

Jupyter Quant is a dockerized environment tailored for quantitative research, equipped with essential tools like statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, numpy, pandas, sci-py, scikit-learn, yellowbricks, shap, optuna, ib_insync, Cython, Numba, bottleneck, numexpr, jedi language server, jupyterlab-lsp, black, isort, and more. It does not include conda/mamba and relies on pip for package installation. The image is optimized for size, includes common command line utilities, supports apt cache, and allows for the installation of additional packages. It is designed for ephemeral containers, ensuring data persistence, and offers volumes for data, configuration, and notebooks. Common tasks include setting up the server, managing configurations, setting passwords, listing installed packages, passing parameters to jupyter-lab, running commands in the container, building wheels outside the container, installing dotfiles and SSH keys, and creating SSH tunnels.

Jupyter Quant is a dockerized environment tailored for quantitative research, equipped with essential tools like statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, numpy, pandas, sci-py, scikit-learn, yellowbricks, shap, optuna, and more. It provides Interactive Broker connectivity via ib_async and includes major Python packages for statistical and time series analysis. The image is optimized for size, includes jedi language server, jupyterlab-lsp, and common command line utilities. Users can install new packages with sudo, leverage apt cache, and bring their own dot files and SSH keys. The tool is designed for ephemeral containers, ensuring data persistence and flexibility for quantitative analysis tasks.

AI Hedge Fund is a proof of concept for an AI-powered hedge fund that explores the use of AI to make trading decisions. The project is for educational purposes only and simulates trading decisions without actual trading. It employs agents like Market Data Analyst, Valuation Agent, Sentiment Agent, Fundamentals Agent, Technical Analyst, Risk Manager, and Portfolio Manager to gather and analyze data, calculate risk metrics, and make trading decisions.

CAMEL is an open-source library designed for the study of autonomous and communicative agents. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments.

Parsee AI is a high-level open source data extraction and structuring framework specialized for the extraction of data from a financial domain, but can be used for other use-cases as well. It aims to make the structuring of data from unstructured sources like PDFs, HTML files, and images as easy as possible. Parsee can be used locally in Python environments or through a hosted version for cloud-based jobs. It supports the extraction of tables, numbers, and other data elements, with the ability to create custom extraction templates and run jobs using different models.

FreeGenius AI is an ambitious project offering a comprehensive suite of AI solutions that mirror the capabilities of LetMeDoIt AI. It is designed to engage in intuitive conversations, execute codes, provide up-to-date information, and perform various tasks. The tool is free, customizable, and provides access to real-time data and device information. It aims to support offline and online backends, open-source large language models, and optional API keys. Users can use FreeGenius AI for tasks like generating tweets, analyzing audio, searching financial data, checking weather, and creating maps.

Deep Lake is a Database for AI powered by a storage format optimized for deep-learning applications. Deep Lake can be used for: 1. Storing data and vectors while building LLM applications 2. Managing datasets while training deep learning models Deep Lake simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in your own cloud and in one place. Deep Lake is used by Intel, Bayer Radiology, Matterport, ZERO Systems, Red Cross, Yale, & Oxford.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

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.

A curated list of awesome Model Context Protocol (MCP) servers that enable AI models to securely interact with local and remote resources through standardized server implementations. The list focuses on production-ready and experimental servers extending AI capabilities through file access, database connections, API integrations, and other contextual services.

MAVIS (Math Visual Intelligent System) is an AI-driven application that allows users to analyze visual data such as images and generate interactive answers based on them. It can perform complex mathematical calculations, solve programming tasks, and create professional graphics. MAVIS supports Python for coding and frameworks like Matplotlib, Plotly, Seaborn, Altair, NumPy, Math, SymPy, and Pandas. It is designed to make projects more efficient and professional.

This repository is a collection of papers on Tabular Large Language Models (LLMs) specialized for processing tabular data. It includes surveys, models, and applications related to table understanding tasks such as Table Question Answering, Table-to-Text, Text-to-SQL, and more. The repository categorizes the papers based on key ideas and provides insights into the advancements in using LLMs for processing diverse tables and fulfilling various tabular tasks based on natural language instructions.

Finance fact-checker with accuracy scoring, using sources like NerdWallet, Investopedia, BEA, and St. Louis Fed.

中文金融行业专家的风调

Investment Co-Pilot: Portfolio backtesting and access to in-depth financial data and historical closing prices of US-listed companies. (Pulse formerly)

I assist you in understanding the details of a company's financial results based on provided earnings data. If you have an earnings report you'd like me to analyze, feel free to share it, and I'll provide detailed insights and interpretations!

Analyzes annual reports, focusing on specific user-provided data

Financial analysis expert for annual report summaries.

The Sign of Money: A SherLockian Quest for Decoding the Financial Market’s Mysteries

DeFi analyst specializing in insightful financial narratives.

Your go-to source for synthesized financial news.

GICS is a classification standard developed by MSCI and S&P Dow Jones Indices. This GPT is not a MSCI and S&P product. Official website : https://www.msci.com/our-solutions/indexes/gics

Expert on Chevron Corp, provides detailed insights in a professional tone.

Theo dõi thị trường

Analyze trading report

Expert in 13F filings analysis backed by specific APIs and 13F Database

BuffettMungerDuan Finance AI' revolutionizes financial analysis, blending Buffett, Munger, and Duan's insights. Advanced algorithms and a vast database empower precise market forecasts and strategies, essential for investors and financial pros

Company Profile Builder and Analyzer

Does some data analysis for you

专注于“投资策略”类型的研报分析总结，提炼对行业配置的核心观点 Focusing on the analysis and summary of research reports on the type of "investment strategy", refining core perspectives on industry allocation

Your expert in limitless, detailed scientific data analysis and reporting

Enhances decision-making by providing insightful data analysis.