Best AI tools for< identify areas where team members need support >

Supermanage AI is a tool that helps managers prepare for 1-on-1 meetings with their team members. It uses AI to analyze public Slack channels and provide insights into each team member's contributions, challenges, and engagement. This information can help managers have more productive and meaningful 1-on-1s.

IMAGINaiTION is a company that uses artificial intelligence (AI) to create solutions for real-world problems. They believe that AI can be used to make the world a more inclusive and equitable place. One of their projects is a Mobile App Accessibility Audit Tool that uses AI to analyze mobile apps and identify areas where accessibility can be improved. This tool is designed to help developers create more accessible apps that can be used by everyone, regardless of their abilities.

Tute.ai is an AI-powered learning platform that provides personalized learning experiences for students. It uses AI to track student progress, identify areas where they need extra support, and provide them with tailored learning materials. Tute.ai also offers a variety of features to help students learn, such as interactive exercises, quizzes, and games.

Fork.ai is a tool that helps businesses identify technologies used in mobile apps. With Fork.ai, businesses can gain insights into their competitors' tech stacks, identify potential partners, and generate leads. Fork.ai's key features include: - Technology identification: Fork.ai can identify over 1,000 technologies used in mobile apps, including programming languages, frameworks, libraries, and SDKs. - Competitor analysis: Fork.ai provides insights into the technologies used by your competitors, allowing you to identify areas where you can gain a competitive advantage. - Lead generation: Fork.ai can help you generate leads by identifying potential customers who are using specific technologies. - Partnership discovery: Fork.ai can help you identify potential partners who are using complementary technologies.

Learnt.ai is an AI-powered learning platform that provides personalized learning experiences for students. It uses artificial intelligence to analyze student data and identify areas where they need additional support. Learnt.ai then creates personalized learning plans that are tailored to each student's individual needs. The platform also provides students with access to a variety of learning resources, including videos, articles, and interactive exercises.

SelfLearner is an AI-powered learning platform that provides personalized learning experiences for students of all ages. The platform uses artificial intelligence to track student progress, identify areas where they need additional support, and provide them with tailored learning materials. SelfLearner also offers a variety of interactive learning activities, such as games, simulations, and quizzes, to help students learn in a fun and engaging way.

A-Levels.ai is an online learning platform that provides students with personalized learning experiences. The platform uses artificial intelligence to track student progress and identify areas where they need additional support. A-Levels.ai also provides students with access to a library of resources, including video lessons, practice questions, and past papers.

Audit.landin.page is an AI-powered tool that helps businesses improve their landing page copywriting. The tool is trained on the principles of behavioral science, decision science, and psychology, and it can help businesses identify areas where their landing page copy can be improved to increase conversions. Audit.landin.page is easy to use, and it provides businesses with detailed feedback on their landing page copy, along with specific recommendations for improvement. The tool is affordable, and it can help businesses of all sizes improve their landing page copy and increase their conversion rates.

Hotjar is a website heatmaps and behavior analytics tool that helps businesses understand how users interact with their websites. It provides a suite of tools to track user behavior, including heatmaps, recordings, surveys, and feedback. Hotjar is used by over 1,306,323 websites in 180+ countries.

AI-Signals is an AI-powered trading indicator that provides traders with real-time insights and advanced algorithms to help them make better trading decisions. The indicator is designed to seamlessly integrate with TradingView charts, providing traders with access to institutional-grade insights and automated analysis. AI-Signals also offers a premium Discord community where traders can access exclusive strategies, trade setups, and market analysis from professional traders.

Amber by inFeedo is an AI-powered employee experience platform that helps organizations collect, analyze, and act on employee feedback. It provides a suite of tools to measure employee engagement, identify areas for improvement, and track progress over time. Amber's AI capabilities enable it to analyze employee feedback in real-time, identify trends and patterns, and provide personalized recommendations to managers. With Amber, organizations can gain a deeper understanding of their employees' needs and create a more positive and productive work environment.

Plerdy is a comprehensive suite of conversion rate optimization tools that helps businesses track, analyze, and convert their website visitors into buyers. With a range of features including website heatmaps, session replay software, pop-up software, website feedback tools, and more, Plerdy provides businesses with the insights they need to improve their website's usability and conversion rates.

InsightCrawl is a website that offers users the ability to gain actionable insights on their website's SEO performance through advanced AI analysis. It is a community-driven and AI-generated SaaS MVP idea.

Satlas is a web application that uses artificial intelligence (AI) to generate geospatial data. This data can be used to track changes in the environment, such as deforestation, the growth of wind farms, and the development of new infrastructure. Satlas is a valuable tool for researchers, policymakers, and anyone else who is interested in understanding how the planet is changing.

We360.ai is an award-winning employee monitoring software that helps businesses track employee productivity, attendance, and time. It offers a range of features such as real-time screenshots, app usage tracking, and detailed reports. We360.ai is designed to help businesses improve efficiency, streamline processes, and make informed decisions.

RightJoin is an AI-powered mock interview platform that helps users prepare for job interviews. It offers personalized interviews tailored to the user's background, role, and company. Users can practice answering common interview questions, receive instant feedback, and identify areas for improvement. RightJoin also provides access to a community of coaches and recruiters for additional support.

Consultan is a free AI-powered tool that helps you practice for consulting interviews. It provides instant expert feedback on your responses and suggests improvements. With Consultan, you can get an unbiased and expert review of your answers to interview questions from top consulting firms like McKinsey, Bain, BCG, and Deloitte.

Rank Math is an AI-powered SEO tool that helps you optimize your website for search engines. It offers a variety of features to help you improve your website's ranking, including keyword research, on-page optimization, and link building. Rank Math also provides detailed analytics to help you track your progress and identify areas for improvement.

WEVO is a user experience (UX) research platform that uses artificial intelligence (AI) to help businesses gather and analyze user feedback. WEVO's AI-powered platform automates many of the tasks associated with UX research, such as data collection, analysis, and reporting. This allows businesses to get accurate and actionable insights into their users' experiences in a fraction of the time it would take to conduct traditional UX research studies.

GymBuddy is an AI-powered workout planner that helps users create personalized and effective workout routines. It uses AI technology to analyze user data and provide tailored exercise recommendations based on their fitness goals and body composition. The app also includes features for tracking progress, monitoring weight, and identifying areas for improvement. With its user-friendly interface and advanced analytics, GymBuddy aims to make fitness accessible and enjoyable for everyone.

fAIr is an open AI-assisted mapping service developed by the Humanitarian OpenStreetMap Team (HOT) to improve mapping efficiency and accuracy for humanitarian purposes. It uses AI models, specifically computer vision techniques, to detect objects like buildings, roads, waterways, and trees from satellite and UAV imagery. The service allows OSM community members to create and train their own AI models for mapping in their region of interest and ensures models are relevant to local communities. Constant feedback loop with local communities helps eliminate model biases and improve model accuracy.

OpenLIT is an OpenTelemetry-native GenAI and LLM Application Observability tool. It's designed to make the integration process of observability into GenAI projects as easy as pie – literally, with just **a single line of code**. Whether you're working with popular LLM Libraries such as OpenAI and HuggingFace or leveraging vector databases like ChromaDB, OpenLIT ensures your applications are monitored seamlessly, providing critical insights to improve performance and reliability.

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.

UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured evaluations (covering language, code, embedding use cases), perform root cause analysis on failure cases and give insights on how to resolve them.

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.

HybridAGI is the first Programmable LLM-based Autonomous Agent that lets you program its behavior using a **graph-based prompt programming** approach. This state-of-the-art feature allows the AGI to efficiently use any tool while controlling the long-term behavior of the agent. Become the _first Prompt Programmers in history_ ; be a part of the AI revolution one node at a time! **Disclaimer: We are currently in the process of upgrading the codebase to integrate DSPy**

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)

Qwen is a series of large language models developed by Alibaba DAMO Academy. It outperforms the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen models outperform the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen-72B achieves better performance than LLaMA2-70B on all tasks and outperforms GPT-3.5 on 7 out of 10 tasks.

Here we will keep track of the AI Game Development Tools, including LLM, Agent, Code, Writer, Image, Texture, Shader, 3D Model, Animation, Video, Audio, Music, Singing Voice and Analytics. 🔥 * Tool (AI LLM) * Game (Agent) * Code * Framework * Writer * Image * Texture * Shader * 3D Model * Avatar * Animation * Video * Audio * Music * Singing Voice * Speech * Analytics * Video Tool

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

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

Do-Not-Answer is an open-source dataset curated to evaluate Large Language Models' safety mechanisms at a low cost. It consists of prompts to which responsible language models do not answer. The dataset includes human annotations and model-based evaluation using a fine-tuned BERT-like evaluator. The dataset covers 61 specific harms and collects 939 instructions across five risk areas and 12 harm types. Response assessment is done for six models, categorizing responses into harmfulness and action categories. Both human and automatic evaluations show the safety of models across different risk areas. The dataset also includes a Chinese version with 1,014 questions for evaluating Chinese LLMs' risk perception and sensitivity to specific words and phrases.

The W3C Cognitive AI Community Group focuses on advancing Cognitive AI through collaboration on defining use cases, open source implementations, and application areas. The group aims to demonstrate the potential of Cognitive AI in various domains such as customer services, healthcare, cybersecurity, online learning, autonomous vehicles, manufacturing, and web search. They work on formal specifications for chunk data and rules, plausible knowledge notation, and neural networks for human-like AI. The group positions Cognitive AI as a combination of symbolic and statistical approaches inspired by human thought processes. They address research challenges including mimicry, emotional intelligence, natural language processing, and common sense reasoning. The long-term goal is to develop cognitive agents that are knowledgeable, creative, collaborative, empathic, and multilingual, capable of continual learning and self-awareness.

I'm BizFix, your guide to business optimization using BPI, 5s methods and AI powered Automations.

Optimizes project outcomes through comprehensive post-project evaluations.

Azeroth Data Sage: A detailed Warcraft Log analysis with direct API access. Give the Sage link to a log, ask a question, and the Data Sage will provide!

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I provide Java interview prep and conduct mock interviews.

Upload disclosure documents, and I will summarize what's going on, identify red flag areas to look closer at, and answer all Q&A!

Just send us an image of a scene from a video work and i will guess the name of the work!

Identify and explain mental models for various scenarios.

Analyzes images to identify landmarks and shares historical insights and captivating facts.

Identify and cherish your vintage

Food diary to help you identify food intolerance

Identify and clarify personal values to cultivate a strong sense of purpose and self-confidence

Identify key claims and sniff past the BS with your personal AI Logic Checker and Fallacy Expert.

I confidently identify plants from photos, diagnose issues, and offer advice.

Enables sales & marketing leadership to identify high-value AI use cases

I identify various rocks from images and advise consulting a geologist for certainty.

This interactive inquiry will help identify your relationship attachment style.

Identify your sources of fear and anger and convert those emotions into concrete next steps. Tested and approved by the real Matt Mochary!

Identify the best SaaS sales organizations. Click on the prompt to receive a full report that includes: G2, Glassdoor, and Repvue reviews.

AI Detector GPT is powered by Winston AI and created to help identify AI generated content. It is designed to help you detect use of AI Writing Chatbots such as ChatGPT, Claude and Bard and maintain integrity in academia and publishing. Winston AI is the most trusted AI content detector.