Best AI tools for< Forecasting Analyst >
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20 - AI tool Sites

Datarails
Datarails is a financial planning and analysis platform for Excel users. It automates data consolidation, reporting, and planning while enabling finance teams to continue using their spreadsheets and financial models. With Datarails, finance teams can save time on repetitive tasks and focus on strategic insights that drive business growth.

Groundsales.ai
Groundsales.ai is an AI-driven sales forecasting tool that empowers businesses to make accurate predictions and optimize sales strategies. By leveraging advanced analytics and scenario modeling, the platform provides real-time insights and trend analysis to help businesses stay ahead in the competitive market. With seamless data integration and a user-friendly interface, Groundsales.ai offers a data-driven evolution for businesses of all sizes, enabling them to make informed decisions and maximize revenue potential.

ASK BOSCO®
ASK BOSCO® is an AI reporting and forecasting platform designed for agencies and retailers. It helps users collect and analyze data to improve decision-making, budget planning, and forecasting accuracy. The platform offers features such as AI reporting, competitor benchmarking, AI budget planning, and data integrations to streamline marketing processes and enhance performance. Trusted by leading brands and agencies, ASK BOSCO® provides personalized insights and recommendations to optimize media spend and drive revenue growth.

Julius AI
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.

Stockpulse
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.

FareTrack
FareTrack is an AI-driven data intelligence solution tailored for the modern air travel industry. It offers accurate, timely, and actionable insights for airline revenue management, distribution, and network operations teams. By leveraging advanced AI technology, FareTrack empowers clients with competitive fare tracking, ancillary pricing insights, open pricing monitoring, and price rank value optimization. The platform also provides comprehensive travel data solutions beyond airfare, including tax breakdowns, historical fare analysis, and trend analysis. With customizable dashboards and API integration, FareTrack enables users to make informed decisions swiftly and stay ahead in the dynamic world of air travel.

Jyotax.ai
Jyotax.ai is an AI-powered tax solution that revolutionizes tax compliance by simplifying the tax process with advanced AI solutions. It offers comprehensive bookkeeping, payroll processing, worldwide tax returns and filing automation, profit recovery, contract compliance, and financial modeling and budgeting services. The platform ensures accurate reporting, real-time compliance monitoring, global tax solutions, customizable tax tools, and seamless data integration. Jyotax.ai optimizes tax workflows, ensures compliance with precise AI tax calculations, and simplifies global tax operations through innovative AI solutions.

Vindey
Vindey is an industry-leading AI-powered CRM platform designed for property management and sales solutions. It offers real-time smart suggestions, automation features, and intelligent sales automation to transform customer experiences. Vindey handles the entire sales pipeline, from lead qualification to deal closing, while providing personalized interactions and seamless lead management. The platform also offers AI-powered payment insights, workflow automation, and tailored solutions for various industries, such as sales, healthcare, real estate, education, and manufacturing.

Trendingly
Trendingly is an AI-powered platform designed to help business leaders anticipate future trends by analyzing vast amounts of data from various sources. The platform leverages state-of-the-art AI technology to provide actionable insights and empower users to make informed decisions based on data-driven foresight.

Inventoro
Inventoro is a smart inventory forecasting and replenishment tool that helps businesses optimize their inventory management processes. By analyzing past sales data, the tool predicts future sales, recommends order quantities, reduces inventory size, identifies profitable inventory items, and ensures customer satisfaction by avoiding stockouts. Inventoro offers features such as sales forecasting, product segmentation, replenishment, system integration, and forecast automations. The tool is designed to help businesses decrease inventory, increase revenue, save time, and improve product availability. It is suitable for businesses of all sizes and industries looking to streamline their inventory management operations.

Clari
Clari is a revenue operations platform that helps businesses track, forecast, and close deals. It provides a unified view of the sales pipeline, allowing teams to identify and address potential problems early on. Clari also uses artificial intelligence to surface insights and recommendations, helping businesses improve their sales performance.

Venture Planner
Venture Planner is an AI-powered platform designed to help users generate professional business plans effortlessly. By answering a series of multiple-choice questions, users can create detailed financial forecasts without the need for typing. The platform is fully bespoke to each user's business, offering automated projections, professional quality plans, and strategy suggestions. With over 50,000 users across 74 industries in 22 countries, Venture Planner leverages cutting-edge AI technology to outpace competitors and provide data-driven insights for informed decision-making.

ToolsGroup
ToolsGroup is an AI-powered supply chain and retail planning application that helps retailers, distributors, and manufacturers enhance the resilience and performance of their operations. Leveraging AI and real-time data, ToolsGroup offers probabilistic planning solutions for demand forecasting, inventory optimization, replenishment, assortment planning, and more. The application automates manual tasks, guides smarter decisions with AI, and delivers outstanding customer experiences with real-time visibility across the enterprise.

WAIR
WAIR is a revolutionary AI-driven digital employee platform designed for enterprise lifestyle retailers. It offers advanced solutions for inventory management, product distribution, content creation, and multilingual translation. WAIR leverages cutting-edge AI technology to optimize forecasting accuracy, reduce inventory levels, and automate supply chain processes, ultimately boosting revenue and margins for businesses.

FutureGPT
FutureGPT is an AI tool that leverages the power of GPT-4 to provide advanced predictive capabilities. Users can enhance their results by utilizing this tool, which offers paid predictions. By enabling JavaScript, users can access the app and explore its features to receive accurate and insightful predictions for various purposes. FutureGPT aims to streamline decision-making processes and optimize outcomes through cutting-edge AI technology.

IndexBox
IndexBox is a market intelligence platform that provides data, tools, and analytics to help businesses make informed decisions. The platform offers a variety of features, including access to market data, predictive modeling, and report generation. IndexBox is used by thousands of companies of all sizes, from startups to Fortune 500s.

Opesway
Opesway is an AI-powered financial planning platform that offers a comprehensive solution to help users achieve financial freedom and manage their wealth effectively. The platform provides tools for retirement planning, investment assessment, budget management, debt analysis, and various forecasting tools. Opesway uses AI technology to simplify financial management, make budgeting and investment decisions, and provide personalized insights. Users can connect to financial institutions, import spending data, customize budgets, forecast retirement, and compare financial plans. The platform also features a personalized AI chatbot powered by OpenAI's ChatGPT model.

OMP
OMP is a supply chain planning solution that accelerates the path to supply chain excellence. It is built on deep industry expertise and powered by AI to deliver tangible results. OMP provides decision-centric planning platform covering demand and supply planning, from strategic to operational levels, tailored to specific industries like chemicals, consumer goods, life sciences, metals, and paper/plastics/packaging.

MarketsandMarkets
MarketsandMarkets is a competitive intelligence and market research platform providing over 10,000 clients worldwide with quantified B2B research and built on the Give principles.

Lily AI
Lily AI is an e-commerce product discovery platform that helps brands increase sales and improve customer experience. It uses artificial intelligence to understand the language of customers and inject it across the retail ecosystem, from search to recommendations to demand forecasting. Lily AI's platform is purpose-built for retail and turns qualitative product attributes into a universal, customer-centered mathematical language with unprecedented accuracy. This results in a depth and scale of attribution that no other solution can match.
20 - Open Source Tools

pytorch-forecasting
PyTorch Forecasting is a PyTorch-based package for time series forecasting with state-of-the-art network architectures. It offers a high-level API for training networks on pandas data frames and utilizes PyTorch Lightning for scalable training on GPUs and CPUs. The package aims to simplify time series forecasting with neural networks by providing a flexible API for professionals and default settings for beginners. It includes a timeseries dataset class, base model class, multiple neural network architectures, multi-horizon timeseries metrics, and hyperparameter tuning with optuna. PyTorch Forecasting is built on pytorch-lightning for easy training on various hardware configurations.

pytorch-forecasting
PyTorch Forecasting is a PyTorch-based package designed for state-of-the-art timeseries forecasting using deep learning architectures. It offers a high-level API and leverages PyTorch Lightning for efficient training on GPU or CPU with automatic logging. The package aims to simplify timeseries forecasting tasks by providing a flexible API for professionals and user-friendly defaults for beginners. It includes features such as a timeseries dataset class for handling data transformations, missing values, and subsampling, various neural network architectures optimized for real-world deployment, multi-horizon timeseries metrics, and hyperparameter tuning with optuna. Built on pytorch-lightning, it supports training on CPUs, single GPUs, and multiple GPUs out-of-the-box.

nixtla
Nixtla is a production-ready generative pretrained transformer for time series forecasting and anomaly detection. It can accurately predict various domains such as retail, electricity, finance, and IoT with just a few lines of code. TimeGPT introduces a paradigm shift with its standout performance, efficiency, and simplicity, making it accessible even to users with minimal coding experience. The model is based on self-attention and is independently trained on a vast time series dataset to minimize forecasting error. It offers features like zero-shot inference, fine-tuning, API access, adding exogenous variables, multiple series forecasting, custom loss function, cross-validation, prediction intervals, and handling irregular timestamps.

Webscout
WebScout is a versatile tool that allows users to search for anything using Google, DuckDuckGo, and phind.com. It contains AI models, can transcribe YouTube videos, generate temporary email and phone numbers, has TTS support, webai (terminal GPT and open interpreter), and offline LLMs. It also supports features like weather forecasting, YT video downloading, temp mail and number generation, text-to-speech, advanced web searches, and more.

LLM-PlayLab
LLM-PlayLab is a repository containing various projects related to LLM (Large Language Models) fine-tuning, generative AI, time-series forecasting, and crash courses. It includes projects for text generation, sentiment analysis, data analysis, chat assistants, image captioning, and more. The repository offers a wide range of tools and resources for exploring and implementing advanced AI techniques.

SolarLLMZeroToAll
SolarLLMZeroToAll is a comprehensive repository that provides a step-by-step guide and resources for learning and implementing Solar Longitudinal Learning Machines (SolarLLM) from scratch. The repository covers various aspects of SolarLLM, including theory, implementation, and applications, making it suitable for beginners and advanced users interested in solar energy forecasting and machine learning. The materials include detailed explanations, code examples, datasets, and visualization tools to facilitate understanding and practical implementation of SolarLLM models.

labo
LABO is a time series forecasting and analysis framework that integrates pre-trained and fine-tuned LLMs with multi-domain agent-based systems. It allows users to create and tune agents easily for various scenarios, such as stock market trend prediction and web public opinion analysis. LABO requires a specific runtime environment setup, including system requirements, Python environment, dependency installations, and configurations. Users can fine-tune their own models using LABO's Low-Rank Adaptation (LoRA) for computational efficiency and continuous model updates. Additionally, LABO provides a Python library for building model training pipelines and customizing agents for specific tasks.

CoachAI-Projects
This repo contains official implementations of **Coach AI Badminton Project** from Advanced Database System Laboratory, National Yang Ming Chiao Tung University supervised by Prof. Wen-Chih Peng. The high-level concepts of each project are as follows: 1. Visualization Platform published at _Physical Education Journal 2020_ aims to construct a platform that can be used to illustrate the data from matches. 2. Shot Influence and Extension Work published at _ICDM-21_ and _ACM TIST 2022_ , respectively introduce a framework with a shot encoder, a pattern extractor, and a rally encoder to capture long short-term dependencies for evaluating players' performance of each shot. 3. Stroke Forecasting published at _AAAI-22_ proposes the first stroke forecasting task to predict the future strokes of both players based on the given strokes by ShuttleNet, a position-aware fusion of rally progress and player styles framework. 4. Strategic Environment published at _AAAI-23 Student Abstract_ designs a safe and reproducible badminton environment for turn-based sports, which simulates rallies with different angles of view and designs the states, actions, and training procedures. 5. Movement Forecasting published at _AAAI-23_ proposes the first movement forecasting task, which contains not only the goal of stroke forecasting but also the movement of players, by DyMF, a novel dynamic graphs and hierarchical fusion model based on the proposed player movements (PM) graphs. 6. CoachAI-Challenge-IJCAI2023 is a badminton challenge (CC4) hosted at _IJCAI-23_. Please find the website for more details. 7. ShuttleSet published at _KDD-23_ is the largest badminton singles dataset with stroke-level records. - An extension dataset ShuttleSet22 published at _IJCAI-24 Demo & IJCAI-23 IT4PSS Workshop_ is also released. 8. CoachAI Badminton Environment published at _AAAI-24 Student Abstract and Demo, DSAI4Sports @ KDD 2023_ is a reinforcement learning (RL) environment tailored for AI-driven sports analytics, offering: i) Realistic opponent simulation for RL training; ii) Visualizations for evaluation; and iii) Performance benchmarks for assessing agent capabilities.

qlib
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.

skyrim
Skyrim is a weather forecasting tool that enables users to run large weather models using consumer-grade GPUs. It provides access to state-of-the-art foundational weather models through a well-maintained infrastructure. Users can forecast weather conditions, such as wind speed and direction, by running simulations on their own GPUs or using modal volume or cloud services like s3 buckets. Skyrim supports various large weather models like Graphcast, Pangu, Fourcastnet, and DLWP, with plans for future enhancements like ensemble prediction and model quantization.

ai-models
The `ai-models` command is a tool used to run AI-based weather forecasting models. It provides functionalities to install, run, and manage different AI models for weather forecasting. Users can easily install and run various models, customize model settings, download assets, and manage input data from different sources such as ECMWF, CDS, and GRIB files. The tool is designed to optimize performance by running on GPUs and provides options for better organization of assets and output files. It offers a range of command line options for users to interact with the models and customize their forecasting tasks.

awesome-weather-models
A catalogue and categorization of AI-based weather forecasting models. This page provides a catalogue and categorization of AI-based weather forecasting models to enable discovery and comparison of different available model options. The weather models are categorized based on metadata found in the JSON schema specification. The table includes information such as the name of the weather model, the organization that developed it, operational data availability, open-source status, and links for further details.

WeatherGFT
WeatherGFT is a physics-AI hybrid model designed to generalize weather forecasts to finer-grained temporal scales beyond the training dataset. It incorporates physical partial differential equations (PDEs) into neural networks to simulate fine-grained physical evolution and correct biases. The model achieves state-of-the-art performance in forecasting tasks at different time scales, from nowcasting to medium-range forecasts, by utilizing a lead time-aware training framework and a carefully designed PDE kernel. WeatherGFT bridges the gap between nowcast and medium-range forecast by extending forecasting abilities to predict accurately at a 30-minute time scale.

Time-LLM
Time-LLM is a reprogramming framework that repurposes large language models (LLMs) for time series forecasting. It allows users to treat time series analysis as a 'language task' and effectively leverage pre-trained LLMs for forecasting. The framework involves reprogramming time series data into text representations and providing declarative prompts to guide the LLM reasoning process. Time-LLM supports various backbone models such as Llama-7B, GPT-2, and BERT, offering flexibility in model selection. The tool provides a general framework for repurposing language models for time series forecasting tasks.

FinRobot
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.

CALF
CALF (LLaTA) is a cross-modal fine-tuning framework that bridges the distribution discrepancy between temporal data and the textual nature of LLMs. It introduces three cross-modal fine-tuning techniques: Cross-Modal Match Module, Feature Regularization Loss, and Output Consistency Loss. The framework aligns time series and textual inputs, ensures effective weight updates, and maintains consistent semantic context for time series data. CALF provides scripts for long-term and short-term forecasting, requires Python 3.9, and utilizes word token embeddings for model training.

LLMsForTimeSeries
LLMsForTimeSeries is a repository that questions the usefulness of language models in time series forecasting. The work shows that simple baselines outperform most language model-based time series forecasting models. It includes ablation studies on LLM-based TSF methods and introduces the PAttn method, showcasing the performance of patching and attention structures in forecasting. The repository provides datasets, setup instructions, and scripts for running ablations on different datasets.

Awesome-LWMs
Awesome Large Weather Models (LWMs) is a curated collection of articles and resources related to large weather models used in AI for Earth and AI for Science. It includes information on various cutting-edge weather forecasting models, benchmark datasets, and research papers. The repository serves as a hub for researchers and enthusiasts to explore the latest advancements in weather modeling and forecasting.

Transformers_And_LLM_Are_What_You_Dont_Need
Transformers_And_LLM_Are_What_You_Dont_Need is a repository that explores the limitations of transformers in time series forecasting. It contains a collection of papers, articles, and theses discussing the effectiveness of transformers and LLMs in this domain. The repository aims to provide insights into why transformers may not be the best choice for time series forecasting tasks.

sktime
sktime is a Python library for time series analysis that provides a unified interface for various time series learning tasks such as classification, regression, clustering, annotation, and forecasting. It offers time series algorithms and tools compatible with scikit-learn for building, tuning, and validating time series models. sktime aims to enhance the interoperability and usability of the time series analysis ecosystem by empowering users to apply algorithms across different tasks and providing interfaces to related libraries like scikit-learn, statsmodels, tsfresh, PyOD, and fbprophet.
20 - OpenAI Gpts

Financial Modeling GPT
Expert in financial modeling for valuation, budgeting, and forecasting.

Ads Incrementality & Campaign Analyst
Expert in ads incrementality and campaign will help you interpret data, forecasting and share you testing frameworks using advanced Python libraries

FORECASTING: PRINCIPLES AND PRACTICE
预测:方法与实践(第三版) Rob J Hyndman 和 George Athanasopoulos 澳大利亚莫纳什大学

Strategic Planning Advisor
Guides financial strategy through data analysis and forecasting.

Australian Financial Legislation Explorer
Expert in comprehensive Australian government income and financial forecasting

Prévisions Cryptos
Prédictif des tendances crypto à partir de la presse et des réseaux sociaux

Prophet Optimizer
Prophet model expert, professional yet approachable, seeks clarification

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