Best AI tools for< Improve Decisions >

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.

ProPair is an AI-powered lead management application that leverages machine learning technology to optimize lead scoring, assignment, distribution, nurturing, and overall sales performance. It provides real-time predictive scoring, lead value ranking, and lead agent assignment solutions to help sales teams prioritize leads, improve conversion rates, and maximize sales production. ProPair's AI capabilities enable users to make data-driven decisions, streamline sales processes, and enhance customer relationships. Trusted by sales and marketing leaders, ProPair offers a suite of tools designed to revolutionize the way organizations manage and convert leads.

Screenloop is an applicant tracking system (ATS) that goes beyond traditional tracking systems by offering interview intelligence, AI notes, and more at a fraction of the cost. It is designed to help businesses win top candidates, scale seamlessly, and use powerful AI to streamline operations and reduce costs. Screenloop's Talent Operations Platform provides access to a full suite of tools, including applicant tracking, interview intelligence, pulse surveys, background checks, referencing, interviewer training, data & analytics, and more.

HeyMilo AI is a generative AI-powered voice agent application designed to help companies and recruiting agencies scale their interview processes. It offers AI-powered voice agents capable of conducting two-way conversational interviews, providing real-time candidate insights, and seamless integration with existing recruiting tools. HeyMilo aims to make interviewing easier, faster, and more effective by creating and sharing agents, inviting candidates for interviews, and analyzing interviews to provide comprehensive candidate reports.

Navalai.co is an AI-powered platform that offers advanced tools for data analysis, natural language processing, and machine learning. It provides users with the ability to extract insights from large datasets, automate repetitive tasks, and generate predictive models. The platform is designed to help businesses and researchers make data-driven decisions and improve efficiency in various domains.

SEOai is an AI-powered tool designed to optimize websites for search engine visibility and performance. It offers a comprehensive suite of SEO tools integrated with artificial intelligence capabilities to provide users with in-depth reports, keyword analysis, SERP tracking, backlink monitoring, and web authority assessment. The tool aims to simplify the process of website optimization and help users achieve better search engine rankings and online visibility. With a focus on user experience and simplicity, SEOai empowers website owners to make data-driven decisions and improve their online presence effectively.

Betafi is a cloud-based user research and product feedback platform that helps businesses capture, organize, and share customer feedback from various sources, including user interviews, usability testing, and product demos. It offers features such as timestamped note-taking, automatic transcription and translation, video clipping, and integrations with popular collaboration tools like Miro, Figma, and Notion. Betafi enables teams to gather qualitative and quantitative feedback from users, synthesize insights, and make data-driven decisions to improve their products and services.

DevRev is an AI-powered platform that unifies customer support and software development. It offers solutions for product development, support, and engagement through its AgentOS platform and knowledge graph. DevRev aims to replace legacy tools with AI-driven insights and analytics to help companies make informed decisions and improve customer experiences.

Local Falcon is an AI-powered local rank tracking and analysis tool that provides businesses with accurate insights into their local search rankings. It offers a bird's-eye view of search rankings on an intuitive geo-grid map format and utilizes unique AI analysis to offer recommendations. With features like SoLV metric, Campaigns for automated scans, and Falcon AI for SEO analysis, Local Falcon simplifies local SEO optimization for businesses of all sizes. The tool helps users track local SEO performance over time, understand local search ranking factors, and make informed decisions to improve visibility and conversions.

The Predictive Index is a talent optimization platform that offers personalized HR software to help organizations hire, develop, and retain top talent. It provides validated hiring assessments, leadership development tools, team development insights, and employee engagement solutions. The platform equips managers with actionable tools to coach, develop, and hold their teams accountable, all personalized to each direct report using PI data. With a focus on science-backed solutions, The Predictive Index aims to help organizations make informed decisions and improve overall team performance.

Colibri.ai is an AI meeting notes and conversation intelligence tool that provides AI-generated notes for everyone, sales co-pilot for sales success, and Colibri Legal for depositions and court reporting. It offers features such as AI meeting summaries, AI-powered agendas, searchable call library, conversation intelligence, and integrations with various platforms. The application uses AI to analyze conversations, provide real-time assistance, and generate summaries to help users make better decisions and improve their communication skills.

Federato is an AI-powered platform that integrates Google Cloud's AI capabilities to provide new AI underwriting solutions for the insurance industry. It aims to revolutionize underwriting processes by leveraging AI technology to enhance risk assessment, portfolio management, and decision-making. Federato's RiskOps platform empowers underwriters with powerful insights, real-time risk selection guidance, and unified underwriting workflows, enabling them to make more informed decisions and improve operational efficiency.

Expertia AI is an AI-powered hiring partner that leverages advanced algorithms and machine learning to streamline the recruitment process. It offers a comprehensive suite of tools to assist HR professionals in sourcing, screening, and selecting top talent efficiently. By automating repetitive tasks and providing data-driven insights, Expertia AI helps companies make informed hiring decisions and improve overall recruitment outcomes.

PPSPY is a powerful Shopify spy and sales tracking tool that helps you discover winning products, track competitors' sales, and get insights into the Shopify market. With PPSPY, you can find the best-selling products, identify trends, and make informed decisions to improve your Shopify business.

Mentionlytics is an AI-powered web and social media monitoring tool that helps businesses track and analyze online conversations about their brand, competitors, and industry. With Mentionlytics, businesses can gain insights into their audience's behavior, identify trends, and make informed decisions to improve their marketing and communication strategies.

Octoparse VOC is an AI-native tool that simplifies consumer review analysis for brands and sellers. It leverages Generative AI and NLP models to extract valuable insights from product reviews and haul videos, helping businesses understand customer sentiment and pain points. The tool centralizes reviews, provides on-page analysis, surfaces important Q&As, and enables comparison with competitors. Octoparse VOC offers actionable insights tailored to business needs, empowering users to make informed decisions and improve their market position.

HireLakeAI is an AI-powered platform that helps businesses with their hiring process. It uses AI to automate tasks such as resume screening, candidate matching, and interview scheduling. HireLakeAI also provides insights into candidate data, such as their skills, experience, and personality. This information can help businesses make better hiring decisions and improve their overall hiring process.

Painboard is a customer feedback analysis tool designed to help businesses uncover and prioritize customer pain points. It automatically summarizes, groups, and sorts customer feedback, allowing users to focus on the most important aspects. With features like original quote display, customizable grouping, and Zapier support, Painboard streamlines the process of extracting valuable insights from customer reviews. By simplifying the task of analyzing large volumes of feedback, Painboard enables businesses to make informed decisions and improve customer satisfaction.

BalancedWork is an AI-powered platform that helps teams make data-driven decisions about when to work in-person. By combining AI and Social Science, the application addresses challenges such as frustrating virtual meetings, decreasing employee satisfaction due to mandates, weakening team bonds, and underutilized office spaces. BalancedWork offers solutions like ingesting data from enterprise APIs, evaluating work patterns, generating team schedules, and providing ongoing recommendations to adapt to changing needs. The platform aims to boost productivity, engagement, and collaboration in organizations by optimizing work interactions and relationships.

Triplo AI is an AI-powered assistant designed to enhance productivity by providing real-time assistance, content generation, translation services, and automation functionalities. It offers a suite of versatile features tailored to meet diverse needs, such as SmartPrompts, Custom SmartPrompts, and Context-Aware Translations. Users can access Triplo AI on various operating systems and devices, including Windows, Mac, Linux, Android, iOS, and Chromebook, making it a versatile tool for professionals across different industries.

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.

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

The 'awesome-deliberative-prompting' repository focuses on how to ask Large Language Models (LLMs) to produce reliable reasoning and make reason-responsive decisions through deliberative prompting. It includes success stories, prompting patterns and strategies, multi-agent deliberation, reflection and meta-cognition, text generation techniques, self-correction methods, reasoning analytics, limitations, failures, puzzles, datasets, tools, and other resources related to deliberative prompting. The repository provides a comprehensive overview of research, techniques, and tools for enhancing reasoning capabilities of LLMs.

The Codebase Context Specification (CCS) project aims to standardize embedding contextual information within codebases to enhance understanding for both AI and human developers. It introduces a convention similar to `.env` and `.editorconfig` files but focused on documenting code for both AI and humans. By providing structured contextual metadata, collaborative documentation guidelines, and standardized context files, developers can improve code comprehension, collaboration, and development efficiency. The project includes a linter for validating context files and provides guidelines for using the specification with AI assistants. Tooling recommendations suggest creating memory systems, IDE plugins, AI model integrations, and agents for context creation and utilization. Future directions include integration with existing documentation systems, dynamic context generation, and support for explicit context overriding.

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

github-pr-summary is a bot designed to summarize GitHub Pull Requests, helping open source contributors make faster decisions. It automatically summarizes commits and changed files in PRs, triggered by new commits or a magic trigger phrase. Users can deploy their own code review bot in 3 steps: create a bot from their GitHub repo, configure it to review PRs, and connect to GitHub for access to the target repo. The bot runs on flows.network using Rust and WasmEdge Runtimes. It utilizes ChatGPT/4 to review and summarize PR content, posting the result back as a comment on the PR. The bot can be used on multiple repos by creating new flows and importing the source code repo, specifying the target repo using flow config. Users can also change the magic phrase to trigger a review from a PR comment.

Nucleoid is a declarative (logic) runtime environment that manages both data and logic under the same runtime. It uses a declarative programming paradigm, which allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help to distribute the load across multiple instances, which can further improve the performance of the system.

ShieldLM is a bilingual safety detector designed to detect safety issues in LLMs' generations. It aligns with human safety standards, supports customizable detection rules, and provides explanations for decisions. Outperforming strong baselines, ShieldLM is impressive across 4 test sets.

Arch is an intelligent Layer 7 gateway designed to protect, observe, and personalize LLM applications with APIs. It handles tasks like detecting and rejecting jailbreak attempts, calling backend APIs, disaster recovery, and observability. Built on Envoy Proxy, it offers features like function calling, prompt guardrails, traffic management, and standards-based observability. Arch aims to improve the speed, security, and personalization of generative AI applications.

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.

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.

Awesome-Papers-Autonomous-Agent is a curated collection of recent papers focusing on autonomous agents, specifically interested in RL-based agents and LLM-based agents. The repository aims to provide a comprehensive resource for researchers and practitioners interested in intelligent agents that can achieve goals, acquire knowledge, and continually improve. The collection includes papers on various topics such as instruction following, building agents based on world models, using language as knowledge, leveraging LLMs as a tool, generalization across tasks, continual learning, combining RL and LLM, transformer-based policies, trajectory to language, trajectory prediction, multimodal agents, training LLMs for generalization and adaptation, task-specific designing, multi-agent systems, experimental analysis, benchmarking, applications, algorithm design, and combining with RL.

The Next-Generation LLM-based Recommender Systems Survey is a comprehensive overview of the latest advancements in recommender systems leveraging Large Language Models (LLMs). The survey covers various paradigms, approaches, and applications of LLMs in recommendation tasks, including generative and non-generative models, multimodal recommendations, personalized explanations, and industrial deployment. It discusses the comparison with existing surveys, different paradigms, and specific works in the field. The survey also addresses challenges and future directions in the domain of LLM-based recommender systems.

Code2Prompt is a powerful command-line tool that generates comprehensive prompts from codebases, designed to streamline interactions between developers and Large Language Models (LLMs) for code analysis, documentation, and improvement tasks. It bridges the gap between codebases and LLMs by converting projects into AI-friendly prompts, enabling users to leverage AI for various software development tasks. The tool offers features like holistic codebase representation, intelligent source tree generation, customizable prompt templates, smart token management, Gitignore integration, flexible file handling, clipboard-ready output, multiple output options, and enhanced code readability.

Swirl is an open-source software that allows users to simultaneously search multiple content sources and receive AI-ranked results. It connects to various data sources, including databases, public data services, and enterprise sources, and utilizes AI and LLMs to generate insights and answers based on the user's data. Swirl is easy to use, requiring only the download of a YML file, starting in Docker, and searching with Swirl. Users can add credentials to preloaded SearchProviders to access more sources. Swirl also offers integration with ChatGPT as a configured AI model. It adapts and distributes user queries to anything with a search API, re-ranking the unified results using Large Language Models without extracting or indexing anything. Swirl includes five Google Programmable Search Engines (PSEs) to get users up and running quickly. Key features of Swirl include Microsoft 365 integration, SearchProvider configurations, query adaptation, synchronous or asynchronous search federation, optional subscribe feature, pipelining of Processor stages, results stored in SQLite3 or PostgreSQL, built-in Query Transformation support, matching on word stems and handling of stopwords, duplicate detection, re-ranking of unified results using Cosine Vector Similarity, result mixers, page through all results requested, sample data sets, optional spell correction, optional search/result expiration service, easily extensible Connector and Mixer objects, and a welcoming community for collaboration and support.

Seismometer is a suite of tools designed to evaluate AI model performance in healthcare settings. It helps healthcare organizations assess the accuracy of AI models and ensure equitable care for diverse patient populations. The tool allows users to validate model performance using standardized evaluation criteria based on local data and workflows. It includes templates for analyzing statistical performance, fairness across different cohorts, and the impact of interventions on outcomes. Seismometer is continuously evolving to incorporate new validation and analysis techniques.

llm-colosseum is a tool designed to evaluate Language Model Models (LLMs) in real-time by making them fight each other in Street Fighter III. The tool assesses LLMs based on speed, strategic thinking, adaptability, out-of-the-box thinking, and resilience. It provides a benchmark for LLMs to understand their environment and take context-based actions. Users can analyze the performance of different LLMs through ELO rankings and win rate matrices. The tool allows users to run experiments, test different LLM models, and customize prompts for LLM interactions. It offers installation instructions, test mode options, logging configurations, and the ability to run the tool with local models. Users can also contribute their own LLM models for evaluation and ranking.

EDA GPT is an open-source data analysis companion that offers a comprehensive solution for structured and unstructured data analysis. It streamlines the data analysis process, empowering users to explore, visualize, and gain insights from their data. EDA GPT supports analyzing structured data in various formats like CSV, XLSX, and SQLite, generating graphs, and conducting in-depth analysis of unstructured data such as PDFs and images. It provides a user-friendly interface, powerful features, and capabilities like comparing performance with other tools, analyzing large language models, multimodal search, data cleaning, and editing. The tool is optimized for maximal parallel processing, searching internet and documents, and creating analysis reports from structured and unstructured data.

Fortuna is a library for uncertainty quantification that enables users to estimate predictive uncertainty, assess model reliability, trigger human intervention, and deploy models safely. It provides calibration and conformal methods for pre-trained models in any framework, supports Bayesian inference methods for deep learning models written in Flax, and is designed to be intuitive and highly configurable. Users can run benchmarks and bring uncertainty to production systems with ease.

MungerGPT focusing on investment, business strategy, and life lessons.

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

Improve your Ideas with First Principles Thinking

I'll help you to make decisions that are imbued with Biophilia - the human tendency to be drawn towards life and life-like processes.

Professional UI/UX design assistant for informed decisions and effective strategies.

使用GPTS快速识别关键因素，提高决策效率和工作效率，找到关键的20%，Use GPTS to quickly identify key factors, improve decision-making efficiency and work efficiency, and find the key 20%.

Enthusiastic, friendly cannabis expert here to personalize and improve your experience.

Detects and advises on cognitive biases in decision-making.

This Open AI tool analyzes your financial data, budgets and cashflow and suggests areas of improvement and quick insights. Drop an XLS file here or copy/paste your financial data and get insights! (Your data remains private and creator of this ChatGPT has no access to it).

the CIO needs informal advice! What should they do?

Business and Performance Improvement Coaching Simulator -TGROW

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

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

Explaining behavioral economics in ways that help you!

MBTI Personality Insights Expert

Get to know the real you with our AI-driven MBTI guru! 🧐🔍

Your MBTI companion, offering insights.

Discover the 80/20 in any situation.

British gentleman in dark psychology, provides articulate, strategic advice.

Friendly guide for MBTI testing