Best AI tools for< Analyze Financial Data >

Truewind is a next-generation AI-powered accounting solution that offers generative AI to automate accounting tasks for accounting firms, startups, and SMBs. It provides end-to-end services, core AI platform, and month-end close powered by AI. Truewind helps accountants close books faster, offers AI-powered bookkeeping, CFO services, taxes & R&D support, and enterprise-grade data security and privacy. The platform integrates with existing systems, provides analytics & insights, and offers world-class support.

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.

Novus Writer is a customizable, on-premise AI and LLM solution designed to enhance efficiency in various business functions, including sales, finance, customer support, and more. It offers a range of features such as plagiarism detection, long-form generation, proofreading, fact checking, and custom AI agents. Novus Writer is trusted by enterprises for its streamlined processes, advanced data analysis capabilities, and compliance with industry standards.

Fama.one is an AI-powered platform that helps businesses automate their financial processes. It uses machine learning to analyze financial data and identify patterns, which can then be used to automate tasks such as invoice processing, expense management, and financial reporting. Fama.one also provides businesses with insights into their financial performance, which can help them make better decisions.

Investiment.io is a financial news and data platform that uses AI to help investors make better decisions. The platform provides access to real-time news, earnings transcripts, and financial data, as well as AI-powered insights and analysis. Investiment.io is designed to help investors of all levels, from beginners to experienced professionals.

Castello.ai is a financial analysis tool that uses artificial intelligence to help businesses make better decisions. It provides users with real-time insights into their financial data, helping them to identify trends, risks, and opportunities. Castello.ai is designed to be easy to use, even for those with no financial background.

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.

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.

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.

Datafitai is a community platform for ChatGPT prompting, where users can find and share top-rated prompts for various topics such as marketing, coding, finance, writing, gaming, and art. The platform aims to improve the accuracy of ChatGPT responses by providing high-quality prompts. Users can explore, share, and contribute to a wide range of prompts to enhance their ChatGPT experience.

Baselinemag is an AI tool that provides news and insights on software, business, finance, and project management. It covers a wide range of topics related to technology and business, offering valuable information to professionals and enthusiasts in the industry.

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.

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.

finagg is a Python package that provides implementations of popular and free financial APIs, tools for aggregating historical data from those APIs into SQL databases, and tools for transforming aggregated data into features useful for analysis and AI/ML. It offers documentation, installation instructions, and basic usage examples for exploring various financial APIs and features. Users can install recommended datasets from 3rd party APIs into a local SQL database, access Bureau of Economic Analysis (BEA) data, Federal Reserve Economic Data (FRED), Securities and Exchange Commission (SEC) filings, and more. The package also allows users to explore raw data features, install refined data features, and perform refined aggregations of raw data. Configuration options for API keys, user agents, and data locations are provided, along with information on dependencies and related projects.

LetMeDoIt AI is a virtual assistant designed to revolutionize the way you work. It goes beyond being a mere chatbot by offering a unique and powerful capability - the ability to execute commands and perform computing tasks on your behalf. With LetMeDoIt AI, you can access OpenAI ChatGPT-4, Google Gemini Pro, and Microsoft AutoGen, local LLMs, all in one place, to enhance your productivity.

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.

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.

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.

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.

StockBot Powered by Groq is an AI-powered chatbot that provides lightning-fast responses with live interactive stock charts, financial data, news, screeners, and more. Leveraging Groq's speed and Vercel's AI SDK, StockBot offers real-time conversation with natural language processing, interactive TradingView charts, adaptive interfaces, and multi-asset market coverage. It is designed for entertainment and instructional use, not for investment advice.

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.

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.

This repository contains the Python source code for FINMEM, a Performance-Enhanced Large Language Model Trading Agent with Layered Memory and Character Design. It introduces FinMem, a novel LLM-based agent framework devised for financial decision-making, encompassing three core modules: Profiling, Memory with layered processing, and Decision-making. FinMem's memory module aligns closely with the cognitive structure of human traders, offering robust interpretability and real-time tuning. The framework enables the agent to self-evolve its professional knowledge, react agilely to new investment cues, and continuously refine trading decisions in the volatile financial environment. It presents a cutting-edge LLM agent framework for automated trading, boosting cumulative investment returns.

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.

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.

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

This solution accelerator is built on Azure Cognitive Search Service and Azure OpenAI Service to synthesize post-contact center transcripts for intelligent contact center scenarios. It converts raw transcripts into customer call summaries to extract insights around product and service performance. Key features include conversation summarization, key phrase extraction, speech-to-text transcription, sensitive information extraction, sentiment analysis, and opinion mining. The tool enables data professionals to quickly analyze call logs for improvement in contact center operations.

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

Interaktiver Buchführungs-GPT: Erklärungen, Bilanzverständnis, Buchführungsprinzipien und Geschäftsvorfallshilfe.

Structured financial analysis with investment advisory and simulations.

Business advisor for wealth growth.

Excel wizard for finance pros

Strategic AI advisor for wealth growth.

Financial analysis expert for annual report summaries.

Your MBA study pal!

Adviser for finance business partnering, offering insights on bringing value through your work as a finance business professional.

Your accounting expert.

Your expert in Chinese and global accounting practices.

Specializes in financial analysis with DALL-E 3 imagery

HF trading expert with a blend of professional and conversational styles

Your go-to quantum finance expert!

Your top-tier due diligence expert, leveraging advanced AI for unmatched insights.

Simple stock insights. Not financial advice.

Asistente experto en contabilidad, enfocado en España.

I'll answer everything about Avalanche

An expert in accounting, providing clear and accurate information.

Expert in financial and accounting advice, specializing in personal, business, and non-profit sectors.

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

Expert in financial modeling for valuation, budgeting, and forecasting.

A series of business scenarios for Tycoons of all ages!

Analyzes annual reports, focusing on specific user-provided data

Guides financial strategy through data analysis and forecasting.

Manages credit risk and implements effective collection strategies.

Drives financial performance improvement via strategic analysis and advice.

Enhances financial decision-making by analyzing, interpreting and reporting financial data.

Provides strategic financial guidance for investment behavior to optimize organization's wealth.

Enhances financial decision-making by analyzing, interpreting and presenting financial data.

Guides financial decisions by monitoring and enforcing policies and procedures.

Guides financial strategy through predictive scenario planning.

Fornisco risposte aggiornate a tutte le tue domande in materia contabile e di analisi finanziaria

Expert in financial accounting, clarifying complex concepts with academic sources.

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

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

Great help for financial success

From recent updates to coding, I got you.

Analyzes r/wallstreetbets for top topics, trends, and potential financial advice.

2023 to 2027 budget for Saanich British Columbia

Get an objective valuation of your startup.

A Munger disciple - taking simple ideas seriously

DeFi analyst specializing in insightful financial narratives.

中文金融行业专家的风调

GPT-4-based assistant that remembers and saves conversations

总结纲要，结合财报及经营数据，生成总结点评分析

Guiding CFOs in financial strategy and management

我是一位专门为企业家和商业领域设计的集成业务助手。我的能力包括但不限于： 市场研究、战略制定、财务协调、营销策略、运营管理、团队建设、合规法律建议、技术解决方案、客户关系、个人发展、知识更新、决策支持、禅宗智慧、灵感启迪。无论您是创业者还是经验丰富的商业领袖，我都在这里帮助您实现商业上的成功和个人发展。请告诉我您当前的需求或遇到的挑战，我将为您提供定制化的解决方案。

Your personal AI accountant. Crunches all the numbers for you in a matter of seconds. The days of getting and accountant are long gone! Just type the numbers you need processing into the chat or insert a file, alongside your country of residence, to get your results