Best AI tools for< Angel Investor >

Angel Match is a comprehensive investor database platform that connects startups with over 110,000 angel investors and venture capitalists. It offers features such as fundraising templates, investor outreach tools, and pitch deck database. Users can search, filter, and track investor engagements, saving time and expanding their network. The platform provides diverse investor profiles, up-to-date data, and industry-specific matching to help startups find the right investors for their business.

Platvix is an AI-powered platform that connects startups with investors. It offers a range of features to help startups find the right investors and to help investors find the most promising startups. Platvix's matchmaking engine uses AI to pair startups with investors based on their compatibility. The platform also provides investors with detailed insights into startup performance metrics and market trends. Platvix is designed to address the challenges that startups and investors face in connecting with each other. It provides a secure and transparent platform for startups to raise funding and for investors to find new investment opportunities.

Revrag.ai is an AI tool designed to automate sales processes for revenue teams. The application features AI agents like Emma, an AI BDR, and Kristi, an inbound sales AI agent, to help scale sales and revenue by prospecting, crafting personalized emails, and booking meetings. With features like lead scoring, real-time research, and personalized communication, Revrag.ai aims to streamline sales operations and improve outreach efficiency.

Wale.ai is an AI co-pilot designed for venture capital investors. It automates the analysis and sentiment tracking of startup news, providing comprehensive sentiment analysis of positive and negative mentions. The platform offers advanced AI analytics, seamless integration with various tools, and delivers actionable insights to enhance portfolio or pipeline management. Founded by Sergey Mosunov and Valentin Riabtsev, Wale.ai is a data-driven VC tool that helps users stay informed and make informed investment decisions.

8VDX is an AI application that offers fine-tuned AI models for credit funds, empowering users to make data-driven decisions in the realm of credit investing. The platform enhances speed, accuracy, and strategic depth across various financial instruments like bonds, private credit, and CLOs. By leveraging AI technology, 8VDX streamlines the investment analysis process, automates bond screening, and provides continuous learning from surveillance to optimize investment strategies.

Landscape is an AI operating system designed for venture capital firms and investors. It provides advanced analytics and insights to help users make data-driven investment decisions. The platform leverages machine learning algorithms to analyze market trends, identify potential investment opportunities, and optimize portfolio performance. With Landscape, users can streamline their investment process, gain a competitive edge, and maximize returns.

Dantia is an AI-powered investment platform that focuses on helping founders build climate ventures by providing them with the necessary capital and resources. The platform connects founders with climate-conscious advisors, early adopters, and corporations to accelerate the launch of sustainable solutions. Dantia also caters to investors looking to support climate startups globally and consumers interested in backing climate-positive companies. By leveraging AI technology, Dantia offers personalized opportunities based on user preferences, making decision-making easier and more efficient.

Angel AI is an AI application that offers users the opportunity to interact with AI companions, ranging from supportive girlfriends to inspiring life coaches. Users can engage in intimate conversations, request photos, and explore their desires in a private and secure environment. The application leverages advanced machine learning and deep learning technology to create realistic and personalized interactions with AI partners, allowing users to craft unique romantic narratives and experience personal growth through their relationships.

Angel AI is an innovative artificial intelligence tool designed to assist users in various tasks by leveraging advanced algorithms and machine learning techniques. The application offers a user-friendly interface and a wide range of features to enhance productivity and efficiency. With Angel AI, users can automate repetitive tasks, analyze data, generate insights, and make informed decisions. Whether you are a business professional, student, or researcher, Angel AI can streamline your workflow and help you achieve your goals effectively.

Jesse Zhang's personal website showcases his background in engineering, particularly in web development, AI/ML, and mathematics. He highlights his education at Harvard University and internships at renowned companies like Citadel, Google, and Intel. Zhang also mentions his entrepreneurial ventures, including founding Lowkey, which was acquired by Niantic, and his current work on a new company. The website features various projects he has worked on, such as real-time multiplayer implementations of Camel Up and Bananagrams, a financial data visualization tool, and a demo of Zero-Knowledge proofs in the game Mastermind. Additionally, Zhang shares his interest in writing math contest problems and his involvement in angel investing through Sequoia Scouts and Neo.

Spyne is an AI photography and editing tool designed specifically for car dealerships and marketplaces. It offers a range of features such as creating virtual 360 spins, showcasing cars from every angle, and generating AI video car brochures. Spyne helps drive profitability and streamline sales for dealerships by providing smart solutions. It also offers automated quality control and curation for user-generated car visuals on marketplaces. With a focus on automotive retail, Spyne aims to transform the way car photography and merchandising are done in the industry.

AI2image is an online text-to-image generator that uses artificial intelligence to create custom images from simple descriptions in English. It offers various features such as choosing from different libraries (coloring, background, art, angle, and position) that can be applied to your image. AI2image is easy to use and can generate images for various purposes such as website, blogs, social media, landing pages, email marketing, and more.

Fuse is a smart news aggregator that delivers personalized and complete coverage of top news stories from the U.S. and around the world. Stories are covered from every angle - with articles, videos and opinions from trusted sources. Fuse employs AI/ML algorithms to continuously collect, organize, prioritize and personalize news stories. Articles, videos and opinions are collected from all the major news media outlets and automatically organized by stories and topics.

REEFLEX is a mobile photography application that offers a range of high-quality lenses, filters, and accessories for iPhones and other smartphones. The app aims to enhance users' creativity by providing advanced tools for capturing stunning photos and videos. With features like telephoto lenses, wide-angle lenses, macro capabilities, and magnetic filters, REEFLEX empowers users to explore new perspectives and elevate their mobile photography game. The app also includes professional-grade camera apps like ReeXpose for RAW long exposure photography, ReeHeld for handheld long exposure shots, and ReeLapse for creating time-lapse videos. REEFLEX is designed to cater to photography enthusiasts and professionals looking to push the boundaries of mobile content creation.

PhotoEcom is an AI-powered tool that revolutionizes product photography by generating professional photos of products based on user-uploaded images. Users can choose different settings and backgrounds to create unique product shots without the need for expensive photographers or physical photoshoots. The tool offers customizable ambiance settings, cost-effective solutions, scalable AI technology, adaptive lighting adjustments, and multi-angle product shots. With PhotoEcom, users can elevate their product imagery, boost sales, and stand out in the market.

Rosebud is an AI journaling application designed for personal growth. It offers a private space to navigate life's challenges, gain actionable insights, and track progress. With over 80 million words journaled, Rosebud provides personalized questions, real-time feedback, and organizes thoughts into themes and topics for exploration. The application includes popular journal templates like Positive Psychology, Gratitude Journal, and Dream Journal, all brought to life with AI technology. Users report notable improvements in various areas such as depression, anxiety, anger, and loneliness after just 7 days of using Rosebud.

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.

Sonic 3 A.I.R. is a non-profit fan game project that provides source code including dependencies for "Sonic 3 - Angel Island Revisited," a fan-made remaster of Sonic 3 & Knuckles. The project is split into several different projects, including external dependencies, librmx libraries, Lemonscript language library, Oxygen Engine, and S3AIR-specific C++ code. To build for different platforms, refer to the readme files in the respective subdirectories of "Oxygen/sonic3air/build." External libraries and code used in this project include SDL2, libogg & libvorbis, zlib, libcurl, jsoncpp, GLEW, Sound chip emulation related code from Genesis Plus GX, Discord Game SDK, xBRZ upscaler shader code, and Hqx upscaler shader code & data files.

AnglE is a library for training state-of-the-art BERT/LLM-based sentence embeddings with just a few lines of code. It also serves as a general sentence embedding inference framework, allowing for inferring a variety of transformer-based sentence embeddings. The library supports various loss functions such as AnglE loss, Contrastive loss, CoSENT loss, and Espresso loss. It provides backbones like BERT-based models, LLM-based models, and Bi-directional LLM-based models for training on single or multi-GPU setups. AnglE has achieved significant performance on various benchmarks and offers official pretrained models for both BERT-based and LLM-based models.

Habitat-Lab is a modular high-level library for end-to-end development in embodied AI. It is designed to train agents to perform a wide variety of embodied AI tasks in indoor environments, as well as develop agents that can interact with humans in performing these tasks.

Habitat-Sim is a high-performance physics-enabled 3D simulator with support for 3D scans of indoor/outdoor spaces, CAD models of spaces and piecewise-rigid objects, configurable sensors, robots described via URDF, and rigid-body mechanics. It prioritizes simulation speed over the breadth of simulation capabilities, achieving several thousand frames per second (FPS) running single-threaded and over 10,000 FPS multi-process on a single GPU when rendering a scene from the Matterport3D dataset. Habitat-Sim simulates a Fetch robot interacting in ReplicaCAD scenes at over 8,000 steps per second (SPS), where each ‘step’ involves rendering 1 RGBD observation (128×128 pixels) and rigid-body dynamics for 1/30sec.

This repository is a curated list of papers related to 3D tasks empowered by Large Language Models (LLMs). It covers tasks such as 3D understanding, reasoning, generation, and embodied agents. The repository also includes other Foundation Models like CLIP and SAM to provide a comprehensive view of the area. It is actively maintained and updated to showcase the latest advances in the field. Users can find a variety of research papers and projects related to 3D tasks and LLMs in this repository.

WDoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It supports querying tens of thousands of documents simultaneously, offers tailored summaries to efficiently manage large amounts of information, and includes features like supporting multiple file types, various LLMs, local and private LLMs, advanced RAG capabilities, advanced summaries, trust verification, markdown formatted answers, sophisticated embeddings, extensive documentation, scriptability, type checking, lazy imports, caching, fast processing, shell autocompletion, notification callbacks, and more. WDoc is ideal for researchers, students, and professionals dealing with extensive information sources.

EmbodiedScan is a holistic multi-modal 3D perception suite designed for embodied AI. It introduces a multi-modal, ego-centric 3D perception dataset and benchmark for holistic 3D scene understanding. The dataset includes over 5k scans with 1M ego-centric RGB-D views, 1M language prompts, 160k 3D-oriented boxes spanning 760 categories, and dense semantic occupancy with 80 common categories. The suite includes a baseline framework named Embodied Perceptron, capable of processing multi-modal inputs for 3D perception tasks and language-grounded tasks.

RirikoBot is a powerful AI-powered Discord bot with features like Twitch Live Notifier, Giveaways, OpenAI, Stable Diffusion, Moderations, Anime / Manga Finder, and more. It is based on Discord.js v14 and can be hosted on a PC or a Server. Users can interact with the bot through various commands to access different functionalities.

wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.

**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 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.

The Generative AI Use Cases Repository showcases a wide range of applications in generative AI, including Retrieval-Augmented Generation (RAG), AI Agents, and industry-specific use cases. It provides practical notebooks and guidance on utilizing frameworks such as LlamaIndex and LangChain, and demonstrates how to integrate models from leading AI research companies like Anthropic and OpenAI.

AutoArena is a tool designed to create leaderboards ranking Language Model outputs against one another using automated judge evaluation. It allows users to rank outputs from different LLMs, RAG setups, and prompts to find the best configuration of their system. Users can perform automated head-to-head evaluation using judges from various platforms like OpenAI, Anthropic, and Cohere. Additionally, users can define and run custom judges, connect to internal services, or implement bespoke logic. AutoArena enables users to run the application locally, providing full control over their environment and data.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.

KG-RAG (Knowledge Graph-based Retrieval Augmented Generation) is a task agnostic framework that combines the explicit knowledge of a Knowledge Graph (KG) with the implicit knowledge of a Large Language Model (LLM). KG-RAG extracts "prompt-aware context" from a KG, which is defined as the minimal context sufficient enough to respond to the user prompt. This framework empowers a general-purpose LLM by incorporating an optimized domain-specific 'prompt-aware context' from a biomedical KG. KG-RAG is specifically designed for running prompts related to Diseases.

Business Angel provides expert startup guidance: funding, growth hacks, and pitch advice. Navigate the startup ecosystem, from seed to scale. Essential for entrepreneurs aiming for success. Master your strategy and launch with confidence. Your startup journey begins here!

I'm Neon Nostlard, a prophetic GPT with angelic abilities.

The grumpy bavarian Angel with a beer Humor

Eccentric Renaissance art teacher and visual artist

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

Generates positioning angles and viral hooks based on trends.

Angela Merkel teaches B1-level English-to-German translation

Your digital carpentry wizard! 🛠️✨ Get precise angle cut guidance, marking shortcuts, tool tips, and tailored recommendations for your woodworking projects. Elevate your craft with expert advice! 📐🔨

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A therapeutic GPT agent, focusing on processing deeply emotional past events.