Best AI tools for< behavioral analyst >

FindYourTriggers is an AI-powered self-awareness enhancer that helps users understand their behavior at the root, strengthen their mindset through self-awareness, and replace bad habits with desired actions. The application offers a three-step plan involving check-ins, trigger analysis, and growth processing to enhance self-awareness and mental health. Users can track their triggers, process them, and overcome challenges with the help of AI technology and personalized assessments.

Audit.Landin.Page is an AI tool designed to help makers improve their landing page copy by leveraging insights from behavioral science, decision science, and psychology. The tool offers a comprehensive audit of landing page copy, providing feedback and recommendations based on 200+ cognitive biases. By analyzing user-provided copy, the tool aims to enhance conversion rates by crafting persuasive and engaging content that resonates with potential customers.

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.

Convin is an omnichannel contact center platform powered by conversation intelligence. It offers a full-stack conversations QA platform for contact centers, AI learning management system for faster agent onboarding, real-time agent assist for improved conversions, automated agent coaching for personalized training, supervisor assist for tracking and assistance, and insights to collect 100% of customer intelligence. The platform also provides automated QA to audit and score customer conversations, analytics for quality management, and a mobile app for on-the-go access. Convin helps businesses in various industries like sales, support, compliance, collection, retention, healthtech, fintech, insurtech, edtech, real estate, hospitality & travel, and BPO to enhance customer interactions and drive revenue.

Woebot Health is an AI-driven enterprise solution for mental health that aims to increase access to mental health support and improve business outcomes. The platform offers a digital companion, Woebot, which provides in-the-moment mental health support through interactive conversations and tools based on elements from Cognitive Behavioral Therapy (CBT), Interpersonal Psychotherapy (IPT), and Dialectical Behavioral Therapy (DBT). Woebot Health also includes a data analytics platform, Population Insights Spotlight, to aggregate insights for clinicians and improve care quality. The application is designed to help individuals develop coping skills for symptoms of anxiety and depression, with a focus on emotional regulation, mood monitoring, and healthy lifestyle choices.

BforeAI is an AI-powered platform that specializes in fighting cyberthreats with intelligence. The platform offers predictive security solutions to prevent phishing, spoofing, impersonation, hijacking, ransomware, online fraud, and data exfiltration. BforeAI uses cutting-edge AI technology for behavioral analysis and predictive results, going beyond reactive blocklists to predict and prevent attacks before they occur. The platform caters to various industries such as financial, manufacturing, retail, and media & entertainment, providing tailored solutions to address unique security challenges.

Traceable is an AI-driven application designed to enhance API security for Cloud-Native Apps. It collects API traffic across the application landscape and utilizes advanced context-based behavioral analytics AI engine to provide insights on APIs, data exposure, threat analytics, and forensics. The platform offers features for API cataloging, activity monitoring, endpoint details, ownership, vulnerabilities, protection against security events, testing, analytics, and more. Traceable also allows for role-based access control, policy configuration, data classification, and integration with third-party solutions for data collection and security. It is a comprehensive tool for API security and threat detection in modern cloud environments.

CEBRA is a machine-learning method that compresses time series data to reveal hidden structures in the variability of the data. It excels in analyzing behavioral and neural data simultaneously, decoding activity from the visual cortex of the mouse brain to reconstruct viewed videos. CEBRA is a novel encoding method that leverages both behavioral and neural data to produce consistent and high-performance latent spaces, allowing for hypothesis testing, label-free usage, and accurate decoding of natural movies from the visual cortex.

Bethge Lab is an AI research group at the University of Tübingen focusing on Neuro AI - Autonomous Lifelong Learning in Machines and Brains. They develop machine learning tools for neural data analysis and draw inspiration from the brain to address key problems in machine learning. Their research includes representation learning, probabilistic inference, generative modeling, behavioral data analysis, and neural data analysis. Additionally, they explore AI sciencepreneurship and collaborate with startups. Bethge Lab aims to advance the understanding of autonomous learning and develop economically feasible solutions for long-term human needs.

Rep AI is an AI-powered eCommerce shopping assistant and Shopify AI chatbot application that aims to boost website conversion rates and handle support requests efficiently. The AI concierge engages visitors at the right moment with personalized conversations, leading to increased sales and customer satisfaction. Rep AI utilizes Behavioral AI to convert browsers into buyers, guides shoppers through the shopping journey, and generates sales even when users are away. It offers features like precise timing engagement, personalized product recommendations, multilingual support, and 24/7 AI concierge services.

Milio is an AI-powered voice-operated Interview Companion that helps users ace their interviews by handling a wide range of questions, from Leetcode to behavioral questions. It adapts quickly to new question types and trends, providing real-time performance feedback. Milio also offers features like answering complex questions, resolving conflicts, and keeping technical skills up-to-date. With a focus on data-driven insights and engagement levels, Milio prioritizes leads and opportunities effectively. The application is designed to elevate interview performance and reduce anxiety, offering all features for a single subscription of $35 per month.

Upshot.ai is an award-winning omnichannel customer engagement, user engagement, and gamification platform that helps businesses improve product adoption and conversions using principles of gamification, behavioral psychology, and learning theory. The platform enables product, digital, and marketing teams to capture user data, analyze it with over 50 analytical reports, create target user segments, improve product and feature adoption through dynamic in-app guidance, achieve highly personalized communication at scale, gamify user experience, build loyal users, upsell and cross-sell, provide in-the-moment experiences, retain users, deliver omni-channel experiences, create automated workflows, and make data-driven decisions using machine learning algorithms.

FALTAH, powered by Velents Ai, is an AI-driven interview simulator designed to help users practice interview questions, enhance their skills, and receive personalized feedback. The platform utilizes artificial intelligence to analyze competences, personality traits, and CV scores, providing insights to improve interview performance. Users can benefit from behavioral interview and skills reports, CV parsing, and job readiness assessments. FALTAH aims to assist students, job seekers, and remote workers in preparing for interviews and standing out in the competitive job market.

CogPrints is an electronic archive for self-archived papers in any area of Psychology, Neuroscience, and Linguistics, and many areas of Computer Science (e.g., artificial intelligence, robotics, vision, learning, speech, neural networks), Philosophy (e.g., mind, language, knowledge, science, logic), Biology (e.g., ethology, behavioral ecology, sociobiology, behavior genetics, evolutionary theory), Medicine (e.g., Psychiatry, Neurology, human genetics, Imaging), Anthropology (e.g., primatology, cognitive ethnology, archeology, paleontology), as well as any other portions of the physical, social and mathematical sciences that are pertinent to the study of cognition.

PrepPro is an AI-powered interview preparation tool designed to help users ace their job interviews. It offers comprehensive interview preparation resources to boost confidence and improve performance during interviews. With a user-friendly interface and structured approach, PrepPro aims to assist individuals in mastering technical questions, enhancing problem-solving skills, and boosting confidence for behavioral interviews. The tool provides self-interview practice, access to AI tools, and unlimited generations to support users in securing their dream job offers.

The website is a platform called Abnormal AI that provides comprehensive email protection against attacks exploiting human behavior, such as phishing and social engineering. It uses AI-native solutions and API-based architecture to deeply understand human behavior, detect email threats, and deliver multi-layered defense. Abnormal AI offers products to secure cloud email, increase productivity with AI, prevent SaaS application attacks, and protect cloud infrastructure. The platform is trusted by Fortune 500 companies and other organizations to combat modern email threats effectively.

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.

Simpleem is an Artificial Emotional Intelligence (AEI) tool that helps users uncover intentions, predict success, and leverage behavior for successful interactions. By measuring all interactions and correlating them with concrete outcomes, Simpleem provides insights into verbal, para-verbal, and non-verbal cues to enhance customer relationships, track customer rapport, and assess team performance. The tool aims to identify win/lose patterns in behavior, guide users on boosting performance, and prevent burnout by promptly identifying red flags. Simpleem uses proprietary AI models to analyze real-world data and translate behavioral insights into concrete business metrics, achieving a high accuracy rate of 94% in success prediction.

Interview Igniter is an AI-powered platform that provides job seekers with a robust interview simulation to fine-tune their skills, adapt to their learning curve, and get detailed feedback. It offers a comprehensive question bank, including industry-specific questions and actual interview questions asked by leading tech companies like Google, Facebook, Apple, and Amazon. Interview Igniter also provides a coding interview tool for practicing and improving coding skills, with interactive guidance and tailored learning experiences. The platform utilizes Conversation Intelligence tools for analyzing communication in real-time and providing nuanced feedback. Interview Igniter was created by Vidal Graupera, a former engineering manager at LinkedIn and Uber with over 20 years of experience hiring.

The OECD Observatory of Public Sector Innovation (OPSI) is a website that provides resources and tools to help governments and public servants explore new possibilities for innovation. OPSI's work areas include European Commission Collaboration, Anticipatory Innovation, Cross-Border Government Innovation, Behavioural Insights, Innovative Capacity, Innovation Trends, Innovation Portfolios, Mission-Oriented Innovation, Innovation Management, and Systems Approaches. OPSI also has a number of resources available, including a Toolkit Navigator, Case Study Library, Portfolio Exploration Tool, and Anticipatory Innovation Resource (AIR).

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

Slips is a powerful endpoint behavioral intrusion prevention and detection system that uses machine learning to detect malicious behaviors in network traffic. It can work with network traffic in real-time, PCAP files, and network flows from tools like Suricata, Zeek/Bro, and Argus. Slips threat detection is based on machine learning models, threat intelligence feeds, and expert heuristics. It gathers evidence of malicious behavior and triggers alerts when enough evidence is accumulated. The tool is Python-based and supported on Linux and MacOS, with blocking features only on Linux. Slips relies on Zeek network analysis framework and Redis for interprocess communication. It offers a graphical user interface for easy monitoring and analysis.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Data-to-paper is an AI-driven framework designed to guide users through the process of conducting end-to-end scientific research, starting from raw data to the creation of comprehensive and human-verifiable research papers. The framework leverages a combination of LLM and rule-based agents to assist in tasks such as hypothesis generation, literature search, data analysis, result interpretation, and paper writing. It aims to accelerate research while maintaining key scientific values like transparency, traceability, and verifiability. The framework is field-agnostic, supports both open-goal and fixed-goal research, creates data-chained manuscripts, involves human-in-the-loop interaction, and allows for transparent replay of the research process.

LLaMA Factory is a unified framework for fine-tuning 100+ large language models (LLMs) with various methods, including pre-training, supervised fine-tuning, reward modeling, PPO, DPO and ORPO. It features integrated algorithms like GaLore, BAdam, DoRA, LongLoRA, LLaMA Pro, LoRA+, LoftQ and Agent tuning, as well as practical tricks like FlashAttention-2, Unsloth, RoPE scaling, NEFTune and rsLoRA. LLaMA Factory provides experiment monitors like LlamaBoard, TensorBoard, Wandb, MLflow, etc., and supports faster inference with OpenAI-style API, Gradio UI and CLI with vLLM worker. Compared to ChatGLM's P-Tuning, LLaMA Factory's LoRA tuning offers up to 3.7 times faster training speed with a better Rouge score on the advertising text generation task. By leveraging 4-bit quantization technique, LLaMA Factory's QLoRA further improves the efficiency regarding the GPU memory.

Momentum is an open-source behavioral auditor for backend code that helps developers generate powerful insights into their codebase. It analyzes code behavior, tests it at every git push, and ensures readiness for production. Momentum understands backend code, visualizes dependencies, identifies behaviors, generates test code, runs code in the local environment, and provides debugging solutions. It aims to improve code quality, streamline testing processes, and enhance developer productivity.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

This repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more. It includes monthly best GenAI papers list, interview resources, free courses, and code repositories/notebooks for developing generative AI applications. The repository is regularly updated with the latest additions to keep users informed and engaged in the field of generative AI.

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.

MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.

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.

The ChatGPT R package provides a set of features to assist in R coding. It includes addins like Ask ChatGPT, Comment selected code, Complete selected code, Create unit tests, Create variable name, Document code, Explain selected code, Find issues in the selected code, Optimize selected code, and Refactor selected code. Users can interact with ChatGPT to get code suggestions, explanations, and optimizations. The package helps in improving coding efficiency and quality by providing AI-powered assistance within the RStudio environment.

Trubrics-sdk is a software development kit designed to facilitate the integration of analytics features into applications. It provides a set of tools and functionalities that enable developers to easily incorporate analytics capabilities, such as data collection, analysis, and reporting, into their software products. The SDK streamlines the process of implementing analytics solutions, allowing developers to focus on building and enhancing their applications' functionality and user experience. By leveraging trubrics-sdk, developers can quickly and efficiently integrate robust analytics features, gaining valuable insights into user behavior and application performance.

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, ...

This repository maintains a list of research papers on LLM-based Multi-Agents, categorized into five main streams: Multi-Agents Framework, Multi-Agents Orchestration and Efficiency, Multi-Agents for Problem Solving, Multi-Agents for World Simulation, and Multi-Agents Datasets and Benchmarks. The repository also includes a survey paper on LLM-based Multi-Agents and a table summarizing the key findings of the survey.

LangWatch is a monitoring and analytics platform designed to track, visualize, and analyze interactions with Large Language Models (LLMs). It offers real-time telemetry to optimize LLM cost and latency, a user-friendly interface for deep insights into LLM behavior, user analytics for engagement metrics, detailed debugging capabilities, and guardrails to monitor LLM outputs for issues like PII leaks and toxic language. The platform supports OpenAI and LangChain integrations, simplifying the process of tracing LLM calls and generating API keys for usage. LangWatch also provides documentation for easy integration and self-hosting options for interested users.

This repository is designed to inject backdoors into Language Model Models (LLMs) for code. The injected backdoors serve as timestamps for the training dataset of the LLMs. The code is randomly generated and includes watermark backdoors to show specific behaviors. A script automatically updates the repository with a new backdoor every month. Validating the existence of the backdoor can infer when the training dataset was collected. The backdoors are constructed in a specific format, and verifying them may require multiple tries. The repository keeps a record of backdoors injected along with associated dates.

Sunnypilot is a fork of comma.ai's openpilot, offering a unique driving experience for over 250+ supported car makes and models with modified behaviors of driving assist engagements. It complies with comma.ai's safety rules and provides features like Modified Assistive Driving Safety, Dynamic Lane Profile, Enhanced Speed Control, Gap Adjust Cruise, and more. Users can install it on supported devices and cars following detailed instructions, ensuring a safe and enhanced driving experience.

Awesome-Attention-Heads is a platform providing the latest research on Attention Heads, focusing on enhancing understanding of Transformer structure for model interpretability. It explores attention mechanisms for behavior, inference, and analysis, alongside feed-forward networks for knowledge storage. The repository aims to support researchers studying LLM interpretability and hallucination by offering cutting-edge information on Attention Head Mining.

Analyzes behavioral data to understand user interactions and preferences, improving product designs.

Expert critical thinker with a background in psychology, behavioral sciences, and intelligence analysis.

Simply type "news" for easy to digest updates in the Healthcare industry, or be as specific as you want and get the top healthcare news from reliable sources. Healthtech, patient care, insurance policies, provider networks, value based care, behavioral health, condition management, therapy.

The use case designer is configured with the latest Data Science and Behavioral Social Science insights to guide you through the process of defining AI and Machine Learning use cases for the ecosystem.Ai platform.

Chat with Psychology of money

A scholarly GPT specializing in neuromarketing and dark patterns.

Insightful advisor on interpersonal dynamics.

SpectrumSupporter guides on autism and educational rights.

A supportive GPT for users with autism, offering clear and patient assistance.

Your tailored guide to special needs education, growth and development.

Creating tailored social stories for people with autism.

Expert in autism development, offering guidance on milestones and support strategies.

Summarizes US politicians' voting behavior on key issues

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

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

Expert in applying game theory to real-world strategic decisions

Get the best out of Shopify Analytics and Shopify GA4 data.

Your assistant for understanding G Analytics data.

Brief, direct insights with Munger's quotes on investing, psychology of human misjudgement, business perspectives

Data analysis and insight tool for SMEs.