Best AI tools for< Find Influencers >

The Bazaarvoice affable.ai platform is an AI-driven influencer marketing solution that helps brands find, manage, and measure creator collaborations. It offers a range of features to help brands connect with the right creators, manage campaigns, and track results. The platform includes a database of over 100,000 creators, advanced search filters, campaign management tools, and reporting dashboards.

HOLLYFY is a collaboration platform for content creators and advertisers. It provides a range of services, including a collaboration platform, digital advertising, design and creative, and website development. HOLLYFY uses artificial intelligence to match content creators with brand marketers, making it easy for brands to find and collaborate with the right influencers. HOLLYFY also offers a managed service for advertisers, which takes care of the entire process of finding and managing brand integrations.

Odeist is an AI-powered social media discovery and engagement solution that helps businesses find, engage, and grow their audience on social media. It uses artificial intelligence to analyze social media data and identify the most relevant influencers, content, and conversations for each business. Odeist then provides businesses with the tools they need to engage with these influencers and audiences, and track their results. With Odeist, businesses can save time and effort on social media marketing, and get better results.

InsightIQ is a leading influencer marketing platform that connects brands with influencers to create successful campaigns. It offers a range of features to help brands find the right influencers, track campaign performance, and measure ROI. InsightIQ's platform is used by some of the world's leading brands, including Unilever, PepsiCo, and Coca-Cola.

Favikon is an AI-powered influencer marketing platform that helps businesses find and manage influencers for their marketing campaigns. It offers a range of features to help businesses with influencer discovery, tracking, and reporting. Favikon's AI-powered discovery feature enables businesses to find influencers across more than 600 specialized niches effortlessly. The platform also provides in-depth profiles of creators to understand their social media influence and popularity. Favikon's AI-powered rankings help businesses identify trending topics, popular formats, and emerging creators within their industry. The platform also offers a tracking feature to stay updated on the latest trends and posts across social media platforms.

eezyCollab is an AI-powered influencer marketing tool that helps businesses find and collaborate with influencers. It uses AI to match businesses with the right influencers for their campaigns, and it also provides a bulk emailing feature to help businesses reach out to multiple influencers at once. eezyCollab is affordable and easy to use, making it a great option for businesses of all sizes.

Influencity is a comprehensive influencer marketing platform that empowers brands, agencies, and e-commerce businesses to streamline their influencer marketing campaigns. The platform offers a wide range of features such as finding influencers, analyzing data, managing relationships, and measuring campaign results. Influencity leverages AI-powered tools to provide fast and accurate insights, helping users make data-driven decisions and optimize their influencer marketing strategies. With a focus on efficiency and effectiveness, Influencity aims to simplify the influencer marketing process and drive sales for businesses of all sizes.

Impulze.ai is an Influencer Analytics Platform designed to help users discover and manage influencers from a vast global database covering Instagram, TikTok, and YouTube. The platform offers AI algorithms that effectively identify the right influencers, allowing users to effortlessly filter influencers based on various criteria such as engagement rate, follower count, location, age, and gender. Additionally, Impulze.ai provides audience analytics, fraud detection, and data-driven matching to help users find the perfect match for their brand. With features like real-time performance metrics, audience filters, and campaign tracking, Impulze.ai streamlines influencer marketing strategies for agencies and marketers, saving time and enhancing brand awareness.

vHub.ai is an AI-powered Influencer Marketing SaaS Platform that offers a comprehensive suite of tools to streamline influencer marketing campaigns. With features like in-depth influencer insights, authenticity assurance, instant campaign analytics, effortless influencer coordination, and tailor-made campaign strategies, vHub.ai aims to revolutionize the way brands collaborate with influencers. The platform boasts a database of 5 million influencers and 100's of influencer marketing agencies, providing users with the perfect influencer at optimal pricing. By leveraging AI search engine capabilities and VQS (vHub Quality Score), vHub.ai ensures genuine connections and successful influencer partnerships. Users can track campaign performance in real-time, manage all types of campaigns, and customize strategies with precision. With a focus on data-driven influencer discovery, authentic campaigns, custom success campaigns, ROI-driven marketing, and streamlined campaign management, vHub.ai empowers brands to maximize their influencer marketing ROI and reach.

Socialfaim is an AI-powered influencer marketing platform that leverages artificial intelligence to help businesses identify and collaborate with influencers to promote their products or services. The platform uses advanced algorithms to analyze social media data and identify the most relevant influencers for a brand's target audience. By automating the influencer discovery and outreach process, Socialfaim streamlines influencer marketing campaigns and helps businesses reach a wider audience more effectively.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

Examor is a website application that allows you to take exams based on your knowledge notes. It helps you to remember what you have learned and written. The application generates a set of questions from the documents you upload, and you can answer them to test your knowledge. Examor also uses GPT to score and validate your answers, and provides you with feedback. The application is still in its early stages of development, but it has the potential to be a valuable tool for learners.

Quantus is a toolkit designed for the evaluation of neural network explanations. It offers more than 30 metrics in 6 categories for eXplainable Artificial Intelligence (XAI) evaluation. The toolkit supports different data types (image, time-series, tabular, NLP) and models (PyTorch, TensorFlow). It provides built-in support for explanation methods like captum, tf-explain, and zennit. Quantus is under active development and aims to provide a comprehensive set of quantitative evaluation metrics for XAI methods.

A curated list of Generative AI projects, tools, artworks, and models

The worker-vLLM repository provides a serverless endpoint for deploying OpenAI-compatible vLLM models with blazing-fast performance. It supports deploying various model architectures, such as Aquila, Baichuan, BLOOM, ChatGLM, Command-R, DBRX, DeciLM, Falcon, Gemma, GPT-2, GPT BigCode, GPT-J, GPT-NeoX, InternLM, Jais, LLaMA, MiniCPM, Mistral, Mixtral, MPT, OLMo, OPT, Orion, Phi, Phi-3, Qwen, Qwen2, Qwen2MoE, StableLM, Starcoder2, Xverse, and Yi. Users can deploy models using pre-built Docker images or build custom images with specified arguments. The repository also supports OpenAI compatibility for chat completions, completions, and models, with customizable input parameters. Users can modify their OpenAI codebase to use the deployed vLLM worker and access a list of available models for deployment.

Tribe AI is a low code tool designed to rapidly build and coordinate multi-agent teams. It leverages the langgraph framework to customize and coordinate teams of agents, allowing tasks to be split among agents with different strengths for faster and better problem-solving. The tool supports persistent conversations, observability, tool calling, human-in-the-loop functionality, easy deployment with Docker, and multi-tenancy for managing multiple users and teams.

WebScout is a versatile tool that allows users to search for anything using Google, DuckDuckGo, and phind.com. It contains AI models, can transcribe YouTube videos, generate temporary email and phone numbers, has TTS support, webai (terminal GPT and open interpreter), and offline LLMs. It also supports features like weather forecasting, YT video downloading, temp mail and number generation, text-to-speech, advanced web searches, and more.

aiograpi is an asynchronous Instagram API wrapper for Python that allows users to interact with various Instagram functionalities such as retrieving public data of users, posts, stories, followers, and following users, managing proxy servers and challenge resolver, login by different methods, managing messages and threads, downloading and uploading various types of content, working with insights, likes, comments, and more. It is designed for testing or research purposes rather than production business use.

This repo contains official implementations of **Coach AI Badminton Project** from Advanced Database System Laboratory, National Yang Ming Chiao Tung University supervised by Prof. Wen-Chih Peng. The high-level concepts of each project are as follows: 1. Visualization Platform published at _Physical Education Journal 2020_ aims to construct a platform that can be used to illustrate the data from matches. 2. Shot Influence and Extension Work published at _ICDM-21_ and _ACM TIST 2022_ , respectively introduce a framework with a shot encoder, a pattern extractor, and a rally encoder to capture long short-term dependencies for evaluating players' performance of each shot. 3. Stroke Forecasting published at _AAAI-22_ proposes the first stroke forecasting task to predict the future strokes of both players based on the given strokes by ShuttleNet, a position-aware fusion of rally progress and player styles framework. 4. Strategic Environment published at _AAAI-23 Student Abstract_ designs a safe and reproducible badminton environment for turn-based sports, which simulates rallies with different angles of view and designs the states, actions, and training procedures. 5. Movement Forecasting published at _AAAI-23_ proposes the first movement forecasting task, which contains not only the goal of stroke forecasting but also the movement of players, by DyMF, a novel dynamic graphs and hierarchical fusion model based on the proposed player movements (PM) graphs. 6. CoachAI-Challenge-IJCAI2023 is a badminton challenge (CC4) hosted at _IJCAI-23_. Please find the website for more details. 7. ShuttleSet published at _KDD-23_ is the largest badminton singles dataset with stroke-level records. - An extension dataset ShuttleSet22 published at _IJCAI-24 Demo & IJCAI-23 IT4PSS Workshop_ is also released. 8. CoachAI Badminton Environment published at _AAAI-24 Student Abstract and Demo, DSAI4Sports @ KDD 2023_ is a reinforcement learning (RL) environment tailored for AI-driven sports analytics, offering: i) Realistic opponent simulation for RL training; ii) Visualizations for evaluation; and iii) Performance benchmarks for assessing agent capabilities.

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)

The AI Toolkit by Ostris is a collection of tools for machine learning, specifically designed for image generation, LoRA (latent representations of attributes) extraction and manipulation, and model training. It provides a user-friendly interface and extensive documentation to make it accessible to both developers and non-developers. The toolkit is actively under development, with new features and improvements being added regularly. Some of the key features of the AI Toolkit include: - Batch Image Generation: Allows users to generate a batch of images based on prompts or text files, using a configuration file to specify the desired settings. - LoRA (lierla), LoCON (LyCORIS) Extractor: Facilitates the extraction of LoRA and LoCON representations from pre-trained models, enabling users to modify and manipulate these representations for various purposes. - LoRA Rescale: Provides a tool to rescale LoRA weights, allowing users to adjust the influence of specific attributes in the generated images. - LoRA Slider Trainer: Enables the training of LoRA sliders, which can be used to control and adjust specific attributes in the generated images, offering a powerful tool for fine-tuning and customization. - Extensions: Supports the creation and sharing of custom extensions, allowing users to extend the functionality of the toolkit with their own tools and scripts. - VAE (Variational Auto Encoder) Trainer: Facilitates the training of VAEs for image generation, providing users with a tool to explore and improve the quality of generated images. The AI Toolkit is a valuable resource for anyone interested in exploring and utilizing machine learning for image generation and manipulation. Its user-friendly interface, extensive documentation, and active development make it an accessible and powerful tool for both beginners and experienced users.

AudioSeal is a method for speech localized watermarking, designed with state-of-the-art robustness and detector speed. It jointly trains a generator to embed a watermark in audio and a detector to detect watermarked fragments in longer audios, even in the presence of editing. The tool achieves top-notch detection performance at the sample level, generates minimal alteration of signal quality, and is robust to various audio editing types. With a fast, single-pass detector, AudioSeal surpasses existing models in speed, making it ideal for large-scale and real-time applications.

DataLine is an AI-driven data analysis and visualization tool designed for technical and non-technical users to explore data quickly. It offers privacy-focused data storage on the user's device, supports various data sources, generates charts, executes queries, and facilitates report building. The tool aims to speed up data analysis tasks for businesses and individuals by providing a user-friendly interface and natural language querying capabilities.

ZenML is an extensible, open-source MLOps framework for creating portable, production-ready machine learning pipelines. By decoupling infrastructure from code, ZenML enables developers across your organization to collaborate more effectively as they develop to production.

This repository provides a systematic and comprehensive review of efficient LLMs research. We organize the literature in a taxonomy consisting of three main categories, covering distinct yet interconnected efficient LLMs topics from **model-centric** , **data-centric** , and **framework-centric** perspective, respectively. We hope our survey and this GitHub repository can serve as valuable resources to help researchers and practitioners gain a systematic understanding of the research developments in efficient LLMs and inspire them to contribute to this important and exciting field.

Find influencers across Instagram, TikTok, and YouTube whose audience aligns with your target demographic to effectively engage with your customers.

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