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.

Beatandraise is an AI-powered platform that offers Equity Research services using AI and ChatGPT technology on SEC Edgar Chat history. The platform allows users to quickly gain insights into their investment process by leveraging AI to extract attributed sources and time series data from documents. Users can sign up for free to access the platform and perform in-depth searches and analyses on SEC filings. Beatandraise aims to streamline the research process for investors by providing accurate and timely information sourced from official documents.

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.

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.

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.

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, up-to-date data, industry research, and more to help users analyze companies and markets effectively.

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.

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.

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.

WiseData is an AI Assistant for Python Data Analytics designed to help Data Analysts and Data Scientists be 2X more productive. It offers features like data transformation with natural language, data visualization with natural language, and data transformation with SQL. WiseData ensures privacy by not sending analyzed data to its server and protects transmitted prompts and suggestions through encryption. It is a valuable tool for simplifying complex data analytics tasks and enhancing productivity.

Julius AI is an advanced AI data analyst tool that allows users to analyze data with computational AI, chat with files to get expert-level insights, create sleek data visualizations, perform modeling and predictive forecasting, solve math, physics, and chemistry problems, generate polished analyses and summaries, save time by automating data work, and unlock statistical modeling without complexity. It offers features like generating visualizations, asking data questions, effortless cleaning, instant data export, creating animations, and supercharging data analysis. Julius AI is loved by over 1,200,000 users worldwide and is designed to help knowledge workers make the most out of their data.

RTutor is an AI tool that leverages OpenAI's powerful large language models to translate natural language into R or Python code for data analysis. Users can upload data files in various formats and request analysis in plain English, receiving results in minutes. The tool is designed for traditional statistics data analysis, where rows represent observations and columns represent variables. RTutor offers a user-friendly interface for exploring data, generating basic plots, and refining analysis through natural language prompts.

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.

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.

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.

Phidata is a framework for building AI Assistants with memory, knowledge, and tools. It enables LLMs to have long-term conversations by storing chat history in a database, provides them with business context by storing information in a vector database, and enables them to take actions like pulling data from an API, sending emails, or querying a database. Memory and knowledge make LLMs smarter, while tools make them autonomous.

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.

Agentic is a standard AI functions/tools library optimized for TypeScript and LLM-based apps, compatible with major AI SDKs. It offers a set of thoroughly tested AI functions that can be used with favorite AI SDKs without writing glue code. The library includes various clients for services like Bing web search, calculator, Clearbit data resolution, Dexa podcast questions, and more. It also provides compound tools like SearchAndCrawl and supports multiple AI SDKs such as OpenAI, Vercel AI SDK, LangChain, LlamaIndex, Firebase Genkit, and Dexa Dexter. The goal is to create minimal clients with strongly-typed TypeScript DX, composable AIFunctions via AIFunctionSet, and compatibility with major TS AI SDKs.

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 does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

This repository contains a collection of articles and tutorials on quantitative finance, including topics such as machine learning, statistical arbitrage, and risk management. The articles are written in a clear and concise style, and they are suitable for both beginners and experienced practitioners. The repository also includes a number of Jupyter notebooks that demonstrate how to use Python for quantitative finance.

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.

This repository includes papers and blogs about Efficient Transformers, Length Extrapolation, Long Term Memory, Retrieval Augmented Generation(RAG), and Evaluation for Long Context Modeling.

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.