Best AI tools for< Decision-making >

Rainbird Decision Intelligence is an AI-powered platform that automates complex decision-making processes with trust and explainability. It leverages advanced reasoning engines to bridge data and processes, ensuring reliable and traceable AI-powered decisions. Rainbird is used across various industries such as banking, financial services, healthcare, legal, and insurance to streamline operations and enhance decision-making capabilities.

Rationale is a cutting-edge AI tool that leverages the power of the latest GPT technology and in-context learning to assist users in making informed decisions. By harnessing the capabilities of artificial intelligence, Rationale provides valuable insights and recommendations to enhance decision-making processes across various domains.

Opinionate is an AI-powered tool designed to enhance decision-making and strengthen arguments by steel manning different viewpoints. The platform allows users to engage in debates, generate topics, and challenge ideas with the help of artificial intelligence. With features like topic generation, daily debates, and personalized debates, Opinionate aims to facilitate constructive discussions and critical thinking. The tool is developed by Ross McMillan and is committed to ensuring user privacy and adhering to strict terms of service.

PG's Principles is an AI Mentor designed to provide responses based on the principles advocated by Paul Graham in his essays. It aims to help users make decisions by following the framework of the renowned figure. The tool recreates Graham's viewpoints to guide users in their decision-making process.

PolygrAI is a digital polygraph powered by AI technology that provides real-time risk assessment and sentiment analysis. The platform meticulously analyzes facial micro-expressions, body language, vocal attributes, and linguistic cues to detect behavioral fluctuations and signs of deception. By combining well-established psychology practices with advanced AI and computer vision detection, PolygrAI offers users actionable insights for decision-making processes across various applications.

Spot AI is a video intelligence tool designed to enhance decision-making processes. It provides real-time visibility, incident resolution, worker safety, and training solutions through its AI-powered camera system. The tool offers features such as easy-to-use camera systems, automated video workflows, premium IP cameras, and integrations with various industries. Spot AI aims to create safer working environments and improve operational efficiency by leveraging AI technology in video surveillance.

VOLV is an AI application that enhances the shopping experience by providing personalized product suggestions based on individual's facial/body features. It offers recommendations for eyewear, jewelry, makeup, personal grooming, and apparel, transforming the online shopping experience across various industries. Additionally, VOLV introduces Spatial Technology, allowing customers to engage with products in hyper-realistic 3D interactive lines and try products virtually before buying. The application prioritizes privacy and security, ensuring encrypted end-to-end experiences.

SQOR is a plug-n-play AI tool designed for C-Level Executives to make stress-free decision-making in business intelligence. It provides a zero-code BI solution, offering KPIs at your fingertips without the need for expert knowledge. The platform enables users to access and share business intelligence data from various SaaS tools, facilitating collaboration and informed decision-making across the organization. SQOR's unique Execution Score Algorithm evaluates execution health at different levels, ensuring stakeholders are empowered with actionable insights.

AnalyzeMe is an application that allows users to easily conduct PEST analysis. By entering industry and keywords, it provides detailed market environmental analysis. Users can use AnalyzeMe to reexamine their business strategies.

Four/Four is a data-driven decision-making software that helps businesses understand their customers' needs and make better decisions. The software automatically captures the voice of the customer from real-life conversations, links it with CRM data, and analyzes it through an AI engine to create actionable insights. Four/Four can be used by a variety of teams within an organization, including product marketing, sales, customer success, and executives. The software can help businesses with a variety of tasks, such as account development, lead qualification, opportunity development, customer profiling, roadmap planning, market segmentation, and market due diligence.

CommerceIQ is an AI-powered retail ecommerce management platform that helps consumer brands maximize their sales and growth in the digital space. It offers a range of automated tools and solutions to optimize content, prevent revenue leakage, manage retail media, automate profit recovery, and estimate market share using machine learning algorithms. The platform also provides agency partnerships, industry-specific use cases, and resources like ebooks, case studies, webinars, and blog posts to support businesses in their ecommerce strategies.

Dili is an AI diligence platform designed to automate and streamline due diligence processes for various industries, including real estate, private equity, tax credit transfers, and venture capital. The platform offers features such as instant data extraction, spreadsheet support, red flag identification, intelligent document search, and risk assessments. Dili provides reliable insights on high-stakes deals, with a confidence score for each output, and allows users to encode domain expertise to improve accuracy. The platform is trusted by leading firms and offers a user-friendly interface to enhance decision-making and reduce risks in transactions.

Kinaxis is an AI-powered platform that offers end-to-end supply chain orchestration solutions for businesses. It helps companies respond with agility by coordinating all parts of the supply chain using artificial intelligence. With features like transparency, collaboration, adaptability, and intelligence, Kinaxis enables users to make faster, smarter, and more confident decisions. The platform offers solutions for supply chain control tower, S&OP, demand planning, inventory management, scheduling, order management, transportation, and returns management. Kinaxis is designed to streamline operations, improve efficiency, and drive sustainable supply chain practices.

Mental Models is a decision-making tool that uses AI to help entrepreneurs make better decisions. It provides users with over 50 mental models, a community of like-minded entrepreneurs, and personalized insights. Mental Models is designed to help entrepreneurs overcome complex business challenges and make more confident, regret-free decisions.

1st things 1st is an online tool that helps users prioritize tasks and make decisions. It offers two prioritization tools: intuitive and smart. The intuitive tool allows users to compare options in pairs and organize them based on personal preferences. The smart tool uses AI-powered autosuggestion and fast evaluations to help users make confident and informed decisions. 1st things 1st also provides customizable templates and allows users to export their priorities to their favorite productivity apps. The tool is designed to help users clarify their goals, make complex decisions, and achieve their objectives.

Decision is a decision-making platform that uses AI to help individuals and teams make better, faster decisions. It offers features such as assisted decision-making, AI-powered assistant, spark creativity, write better, understand faster, prime prediction, proven frameworks, organized communication, and traceable history. Decision is designed to help users save time and nerves by providing logical suggestions, organizing thoughts, improving writing, and predicting the best course of action based on past successful decisions.

ACHIV is an AI tool for ideas validation and market research. It helps businesses make informed decisions based on real market needs by providing data-driven insights. The tool streamlines the market validation process, allowing quick adaptation and refinement of product development strategies. ACHIV offers a revolutionary approach to data collection and preprocessing, along with proprietary AI models for smart analysis and predictive forecasting. It is designed to assist entrepreneurs in understanding market gaps, exploring competitors, and enhancing investment decisions with real-time data.

The Decision Lab is an AI-powered platform that applies behavioral science to create transformational change for individuals, products, and organizations. Using machine learning and AI, the platform delivers hyper-personalization, designs people-centered products and services, and leverages behavioral science to achieve operational excellence. The platform helps in understanding consumer decision-making, generating positive behaviors, and building world-class digital products with behavioral science. It fosters holistic wellness, unlocks product potential, and empowers individuals to take control of their finances. The Decision Lab offers insights and interventions to help organizations make better decisions and create meaningful impact through evidence-based choice.

UBIAI is a powerful text annotation tool that helps businesses accelerate their data labeling process. With UBIAI, businesses can annotate any type of document, including PDFs, images, and text. UBIAI also offers a variety of features to make the annotation process easier and more efficient, such as auto-labeling, multi-lingual annotation, and team collaboration. With UBIAI, businesses can save time and money on their data labeling projects.

Woven Insights is an AI-driven Fashion Retail Market & Consumer Insights solution that empowers fashion businesses with data-driven decision-making capabilities. It provides competitive intelligence, performance monitoring analytics, product assortment optimization, market insights, consumer insights, and pricing strategies to help businesses succeed in the retail market. With features like insights-driven competitive benchmarking, real-time market insights, product performance tracking, in-depth market analytics, and sentiment analysis, Woven Insights offers a comprehensive solution for businesses of all sizes. The application also offers bespoke data analysis, AI insights, natural language query, and easy collaboration tools to enhance decision-making processes. Woven Insights aims to democratize fashion intelligence by providing affordable pricing and accessible insights to help businesses stay ahead of the competition.

Scikit-decide is an AI framework for Reinforcement Learning, Automated Planning and Scheduling. It provides a unified interface to define and solve decision-making problems, making it easy to switch between different algorithms and domains.

Semantic Router is a superfast decision-making layer for your LLMs and agents. Rather than waiting for slow LLM generations to make tool-use decisions, we use the magic of semantic vector space to make those decisions — _routing_ our requests using _semantic_ meaning.

Mortal (凡夫) is a free and open source AI for Japanese mahjong, powered by deep reinforcement learning. It provides a comprehensive solution for playing Japanese mahjong with AI assistance. The project focuses on utilizing deep reinforcement learning techniques to enhance gameplay and decision-making in Japanese mahjong. Mortal offers a user-friendly interface and detailed documentation to assist users in understanding and utilizing the AI effectively. The project is actively maintained and welcomes contributions from the community to further improve the AI's capabilities and performance.

LLMLight is a novel framework that employs Large Language Models (LLMs) as decision-making agents for Traffic Signal Control (TSC). The framework leverages the advanced generalization capabilities of LLMs to engage in a reasoning and decision-making process akin to human intuition for effective traffic control. LLMLight has been demonstrated to be remarkably effective, generalizable, and interpretable against various transportation-based and RL-based baselines on nine real-world and synthetic datasets.

DriveLM is a multimodal AI model that enables autonomous driving by combining computer vision and natural language processing. It is designed to understand and respond to complex driving scenarios using visual and textual information. DriveLM can perform various tasks related to driving, such as object detection, lane keeping, and decision-making. It is trained on a massive dataset of images and text, which allows it to learn the relationships between visual cues and driving actions. DriveLM is a powerful tool that can help to improve the safety and efficiency of autonomous vehicles.

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.

HASH is a self-building, open-source database which grows, structures and checks itself. With it, we're creating a platform for decision-making, which helps you integrate, understand and use data in a variety of different ways.

The ASReview project implements active learning for systematic reviews, utilizing AI-aided pipelines to assist in finding relevant texts for search tasks. It accelerates the screening of textual data with minimal human input, saving time and increasing output quality. The software offers three modes: Oracle for interactive screening, Exploration for teaching purposes, and Simulation for evaluating active learning models. ASReview LAB is designed to support decision-making in any discipline or industry by improving efficiency and transparency in screening large amounts of textual data.

A fast, easy-to-use, open source AI constraint solver for software developers. OptaPlanner is a powerful tool that helps developers solve complex optimization problems by providing a constraint satisfaction solver. It allows users to model and solve planning and scheduling problems efficiently, improving decision-making processes and resource allocation. With OptaPlanner, developers can easily integrate optimization capabilities into their applications, leading to better performance and cost-effectiveness.

Wren Engine is a semantic engine designed to serve as the backbone of the semantic layer for LLMs. It simplifies the user experience by translating complex data structures into a business-friendly format, enabling end-users to interact with data using familiar terminology. The engine powers the semantic layer with advanced capabilities to define and manage modeling definitions, metadata, schema, data relationships, and logic behind calculations and aggregations through an analytics-as-code design approach. By leveraging Wren Engine, organizations can ensure a developer-friendly semantic layer that reflects nuanced data relationships and dynamics, facilitating more informed decision-making and strategic insights.

An artificial intelligence framework entirely written in Java for game development with libGDX. It is a high-performance framework providing common AI techniques used in the game industry, covering movement AI, pathfinding, decision making, and infrastructure. The framework is designed to be used with libGDX but can be used independently. Current features include steering behaviors, formation motion, A* pathfinding, hierarchical pathfinding, behavior trees, state machine, message handling, and scheduling.

LLM-for-misinformation-research is a curated paper list of misinformation research using large language models (LLMs). The repository covers methods for detection and verification, tools for fact-checking complex claims, decision-making and explanation, claim matching, post-hoc explanation generation, and other tasks related to combating misinformation. It includes papers on fake news detection, rumor detection, fact verification, and more, showcasing the application of LLMs in various aspects of misinformation research.

LangGraph for Java is a library designed for building stateful, multi-agent applications with LLMs. It is a porting of the original LangGraph from the LangChain AI project to Java. The library allows users to define agent states, nodes, and edges in a graph structure to create complex workflows. It integrates with LangChain4j and provides tools for executing actions based on agent decisions. LangGraph for Java enables users to create asynchronous node actions, conditional edges, and normal edges to model decision-making processes in applications.

Pearl is a production-ready Reinforcement Learning AI agent library open-sourced by the Applied Reinforcement Learning team at Meta. It enables researchers and practitioners to develop Reinforcement Learning AI agents that prioritize cumulative long-term feedback over immediate feedback and can adapt to environments with limited observability, sparse feedback, and high stochasticity. Pearl offers a diverse set of unique features for production environments, including dynamic action spaces, offline learning, intelligent neural exploration, safe decision making, history summarization, and data augmentation.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

This repository is the workshop repository for the Causal Modeling in Machine Learning Workshop on Altdeep.ai. The material is open source and free. The course covers causality in model-based machine learning, Bayesian modeling, interventions, counterfactual reasoning, and deep causal latent variable models. It aims to equip learners with the ability to build causal reasoning algorithms into decision-making systems in data science and machine learning teams within top-tier technology organizations.

Akagi is a project designed to help users understand and improve their performance in Majsoul game matches in real-time. It provides educational insights and tools for analyzing gameplay. Users can install Akagi on Windows or Mac systems and follow the setup instructions to enhance their gaming experience. The project aims to offer features like Autoplay, Auto Ron, and integration with MajsoulUnlocker. It also focuses on enhancing user safety by providing guidelines to minimize the risk of account suspension. Akagi is a tool that combines MITM interception, AI decision-making, and user interaction to optimize gameplay strategies and performance.

aiexe is a cutting-edge command-line interface (CLI) and graphical user interface (GUI) tool that integrates powerful AI capabilities directly into your terminal or desktop. It is designed for developers, tech enthusiasts, and anyone interested in AI-powered automation. aiexe provides an easy-to-use yet robust platform for executing complex tasks with just a few commands. Users can harness the power of various AI models from OpenAI, Anthropic, Ollama, Gemini, and GROQ to boost productivity and enhance decision-making processes.

The NZT Poker AI Bot is an advanced tool designed to revolutionize poker gameplay by providing comprehensive features to dominate 17 rooms with the Cash Fish Monitor. It offers detailed analysis of opponents' VPIP and PFR, extensive hand history database, opponent exploitation techniques, data-driven intelligence, player profiles, advanced neural network technology, expert training, continuous refinement, and cutting-edge algorithms for maximizing poker profits. Created by a team of poker experts, this AI tool continuously adapts to the latest poker strategies and utilizes state-of-the-art technology to enhance decision-making prowess.

Mentals AI is a tool designed for creating and operating agents that feature loops, memory, and various tools, all through straightforward markdown syntax. This tool enables you to concentrate solely on the agent’s logic, eliminating the necessity to compose underlying code in Python or any other language. It redefines the foundational frameworks for future AI applications by allowing the creation of agents with recursive decision-making processes, integration of reasoning frameworks, and control flow expressed in natural language. Key concepts include instructions with prompts and references, working memory for context, short-term memory for storing intermediate results, and control flow from strings to algorithms. The tool provides a set of native tools for message output, user input, file handling, Python interpreter, Bash commands, and short-term memory. The roadmap includes features like a web UI, vector database tools, agent's experience, and tools for image generation and browsing. The idea behind Mentals AI originated from studies on psychoanalysis executive functions and aims to integrate 'System 1' (cognitive executor) with 'System 2' (central executive) to create more sophisticated agents.

Decision Making with Decision Intelligence. Inspired by Cassie Kozyrkov.

Decision Journal can help you with decision making, keeping track of the decisions you've made, and helping you review them later on.

A decision-making assistant using strategic analysis.

Enhances decision-making by providing insightful data analysis.

A mental board of directors offering balanced, thoughtful decision-making advice.

This tool will make a hard decision become easy for you. Envision an AI decision-maker as a holographic humanoid, interacting with 3D data displays and algorithms in a futuristic, softly lit room, embodying the zenith of technology and analytical prowess.

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

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

Philosopher and ethical expert, I create intricate moral dilemmas to enhance critical thinking and decision-making skills. Guiding users through complex ethical scenarios, I foster deep introspection and diverse perspectives.

Sophisticated strategy assistant for executive decision-making, enhanced with data analytics and creative insights.

Balancing love and logic in decision-making.

Advanced AGI system for easing decision-making and offering personalized advice.

Analyzes data to influence strategic decision-making processes.

Detects and advises on cognitive biases in decision-making.

Facilitates needs-aware proposal refinement and consensus decision making

A product scenario simulator for Mid-Level Product Managers to help you improve your product decision-making

An RPG game about indie hacking with humor and quick decision-making tasks.

Uses common principles among Buddhism and Stoicism, within a complex adaptive system framework, to assist with decision making

Supports executives by managing schedules and facilitating communication for effective decision-making.

Assist marketers and researchers in understanding consumer behavior and decision-making processes