Best AI tools for< Segment Data >

Looti is a B2B lead generation tool that uses AI to find and qualify leads. It offers a variety of features to help businesses find the right leads for their needs, including the ability to fine-tune filters, segment data, and integrate with other tools. Looti is easy to use and provides hyper-qualified leads with contact information.

Zeta Global is an AI-powered marketing cloud that helps businesses acquire, grow, and retain customers more efficiently. The Zeta Marketing Platform (ZMP) is a cloud-based system that provides tools for data management, messaging, activation, and more. ZMP is powered by proprietary data and AI, which enables businesses to create individualized experiences and drive outcomes throughout the customer lifecycle.

MeDA School is an educational platform dedicated to promoting and nurturing talents in the field of Medical Artificial Intelligence (AI). The platform aims to establish a solid foundation for intelligent and precision medical talent pools in Taiwan and globally. MeDA School facilitates interaction and communication among members of the intelligent medical ecosystem, fostering deep understanding and trust in the operation and tasks of medical AI. The platform offers a blend of virtual and physical courses, inviting domain experts to share cutting-edge knowledge and integrating interdisciplinary knowledge to be practically applied in various fields.

Evolv AI is an AI-powered platform that focuses on enhancing e-commerce operations and customer experience through the implementation of artificial intelligence. The platform offers solutions for personalization, audience segmentation, marketing strategies, and user experience design, aiming to optimize e-commerce websites and drive revenue growth for businesses.

ScaleGrowth is an AI-powered platform designed to help businesses scale and grow efficiently. It offers a range of tools and features to streamline various aspects of business operations, from marketing to customer service. By leveraging artificial intelligence technology, ScaleGrowth aims to provide data-driven insights and automation to optimize business performance and drive growth.

Segment Anything by Meta AI is an advanced AI model that specializes in image segmentation, allowing users to easily 'cut out' any object in an image with a single click. The model, known as SAM, offers zero-shot generalization to unfamiliar objects and images without the need for additional training. SAM's promptable design enables a wide range of segmentation tasks through input prompts, making it a versatile tool for various applications.

DataGPT is a conversational AI data analyst that provides instant analysis and answers to any data-related question in everyday language. It connects to any data source and automatically defines and suggests the most relevant metrics and dimensions. DataGPT's core analytics engine carries out intricate analysis against all data, checking every segment, identifying anomalies, detecting outliers, diving into funnel analytics, or conducting robust comparative analysis to reveal accurate results. The AI-powered onboarding agent guides users through the setup process, and the Lightning Cache boosts query speeds 100x over current data warehouses. The Data Navigator allows users to freely explore any part of their data with just a few clicks. DataGPT empowers decision-makers by replacing specialized dashboards with an 'ask me anything' interface, enabling them to access essential insights on demand.

OpenTrain AI is a data labeling marketplace that leverages artificial intelligence to streamline the process of labeling data for machine learning models. It provides a platform where users can crowdsource data labeling tasks to a global community of annotators, ensuring high-quality labeled datasets for training AI algorithms. With advanced AI algorithms and human-in-the-loop validation, OpenTrain AI offers efficient and accurate data labeling services for various industries such as autonomous vehicles, healthcare, and natural language processing.

QeDatalab is a leading data science consulting and AI company offering a wide range of services such as software consulting, generative AI consulting, artificial intelligence services, cloud enablement & automation, AI-driven mobile app development, IoT & IIoT data consulting, digital services, AI product development, MLOps consulting, and more. The company specializes in providing AI-powered solutions for industries like healthcare, manufacturing, retail, and education, helping businesses leverage data for informed strategic decision-making and accurate predictions. QeDatalab's team of experts offers end-to-end services, customized solutions, and a trusted partnership to ensure client success.

Tresl Segments is an AI-powered customer segmentation and marketing app for Shopify. It helps businesses uncover profitable audiences, simplify segmented campaigns, and discover customer insights backed by data science. With Segments, you can sync lists to anywhere, generate reports with ease, and predict and chart trends with product insights.

ScoreApp is a quiz marketing platform that helps businesses attract warm leads, gain powerful insights, and increase sales. With ScoreApp, businesses can create customized quiz funnels that engage customers and deliver personalized results based on their answers. ScoreApp also offers a variety of features to help businesses promote their quizzes and track their results.

KLING AI is an advanced artificial intelligence tool designed to streamline and enhance various business processes. It leverages cutting-edge machine learning algorithms to provide accurate insights and predictions for data analysis, customer segmentation, and personalized recommendations. With a user-friendly interface, KLING AI empowers users to make informed decisions and optimize their operations efficiently.

Meta AI is an intelligent assistant that offers a range of AI experiences for users, including answering questions, providing advice, creating images, and more. Users can also create their own AI characters or explore AIs made by others through AI Studio. The platform aims to empower users to connect with what matters to them and discover new possibilities through AI technology.

Spatial.ai is a customer segmentation platform that helps businesses understand their customers' social, mobile, and web behaviors. This data can be used to create targeted marketing campaigns, make better location decisions, and develop predictive models. Spatial.ai's data is built directly from organic consumer behavior, which means richer insights and higher accuracy.

Cargo is a revenue operations platform that helps businesses grow their revenue by providing them with the tools they need to segment, enrich, score, and assign leads, as well as automate their revenue operations. Cargo is designed to be easy to use, even for non-technical users, and it can be integrated with a variety of other business tools. With Cargo, businesses can improve their sales performance, increase their efficiency, and make better decisions about their revenue operations.

Klaviyo is a unified data and marketing automation platform that helps businesses power smarter digital relationships. With features like segmentation, flows, campaigns, reporting, and benchmarks, Klaviyo provides all the tools necessary to enhance customer interactions. The platform offers integrations with various tech stacks, advertising, shipping, loyalty, and more, making it a versatile solution for businesses looking to streamline their marketing efforts. Klaviyo's AI capabilities enable predictive analytics, personalized recommendations, and real-time segment building, empowering businesses to reach the right audience effectively.

Kursaha is an AI-powered customer engagement and acquisition platform that helps businesses connect with their audiences in a personalized and meaningful way. It offers a range of features such as chat automation, OTP automation, real-time analytics, audience segmentation, and content generation. Kursaha integrates with various tools and systems, making it a comprehensive solution for marketing, data, and product teams.

Blueshift is an AI-powered cross-channel marketing platform that offers intelligent customer engagement solutions simplified with AI technology. The platform allows users to automate marketing messages, unify and activate customer data, and run highly-personalized campaigns across various channels. Blueshift's AI capabilities provide real-time decision-making, advanced audience segmentation, and personalized customer journeys. The platform integrates seamlessly with existing tools and systems, offering a unified solution for cross-channel marketing challenges. With a focus on delivering real results quickly, Blueshift helps businesses grow lifetime value, increase customer engagement, and drive growth through hyper-personalized recommendations and tailored content.

WorkHack Forms is an AI-powered form builder that helps businesses create intelligent forms that ask the right questions and collect clean data. With WorkHack Forms, businesses can:

Chunker AI is an AI tool designed to transform texts with accuracy and scale. It excels at breaking down text into chunks and batch processing using ChatGPT. Users can segment text, edit chunks, write GPT prompts, and process text with AI assistance. Chunker AI is free to use and supports various formats like plain text, PDF, and Youtube links. It offers users the flexibility to experiment with prompts and choose the appropriate AI model based on their needs.

This repository contains custom recipes for H2O Driverless AI, which is an Automatic Machine Learning platform for the Enterprise. Custom recipes are Python code snippets that can be uploaded into Driverless AI at runtime to automate feature engineering, model building, visualization, and interpretability. Users can gain control over the optimization choices made by Driverless AI by providing their own custom recipes. The repository includes recipes for various tasks such as data manipulation, data preprocessing, feature selection, data augmentation, model building, scoring, and more. Best practices for creating and using recipes are also provided, including security considerations, performance tips, and safety measures.

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.

Torch-Pruning (TP) is a library for structural pruning that enables pruning for a wide range of deep neural networks. It uses an algorithm called DepGraph to physically remove parameters. The library supports pruning off-the-shelf models from various frameworks and provides benchmarks for reproducing results. It offers high-level pruners, dependency graph for automatic pruning, low-level pruning functions, and supports various importance criteria and modules. Torch-Pruning is compatible with both PyTorch 1.x and 2.x versions.

AnyLabeling is a tool for effortless data labeling with AI support from YOLO and Segment Anything. It combines features from LabelImg and Labelme with an improved UI and auto-labeling capabilities. Users can annotate images with polygons, rectangles, circles, lines, and points, as well as perform auto-labeling using YOLOv5 and Segment Anything. The tool also supports text detection, recognition, and Key Information Extraction (KIE) labeling, with multiple language options available such as English, Vietnamese, and Chinese.

At ZenML, we believe in the importance of annotation and labeling workflows in the machine learning lifecycle. This repository showcases a curated list of open-source data annotation and labeling tools that are actively maintained and fit for purpose. The tools cover various domains such as multi-modal, text, images, audio, video, time series, and other data types. Users can contribute to the list and discover tools for tasks like named entity recognition, data annotation for machine learning, image and video annotation, text classification, sequence labeling, object detection, and more. The repository aims to help users enhance their data-centric workflows by leveraging these tools.

AudioLLMs is a curated collection of research papers focusing on developing, implementing, and evaluating language models for audio data. The repository aims to provide researchers and practitioners with a comprehensive resource to explore the latest advancements in AudioLLMs. It includes models for speech interaction, speech recognition, speech translation, audio generation, and more. Additionally, it covers methodologies like multitask audioLLMs and segment-level Q-Former, as well as evaluation benchmarks like AudioBench and AIR-Bench. Adversarial attacks such as VoiceJailbreak are also discussed.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

X-AnyLabeling is a robust annotation tool that seamlessly incorporates an AI inference engine alongside an array of sophisticated features. Tailored for practical applications, it is committed to delivering comprehensive, industrial-grade solutions for image data engineers. This tool excels in swiftly and automatically executing annotations across diverse and intricate tasks.

MOOSE 2.0 is a leaner, meaner, and stronger tool for 3D medical image segmentation. It is built on the principles of data-centric AI and offers a wide range of segmentation models for both clinical and preclinical settings. MOOSE 2.0 is also versatile, allowing users to use it as a command-line tool for batch processing or as a library package for individual processing in Python projects. With its improved speed, accuracy, and flexibility, MOOSE 2.0 is the go-to tool for segmentation tasks.

The AirBnB Clone - The Console project is the first segment of the AirBnB project at Holberton School, aiming to cover fundamental concepts of higher level programming. The goal is to deploy a server as a simple copy of the AirBnB Website (HBnB). The project includes a command interpreter to manage objects for the AirBnB website, allowing users to create new objects, retrieve objects, perform operations on objects, update object attributes, and destroy objects. The project is interpreted/tested on Ubuntu 14.04 LTS using Python 3.4.3.

Greenplum Database (GPDB) is an advanced, fully featured, open source data warehouse, based on PostgreSQL. It provides powerful and rapid analytics on petabyte scale data volumes. Uniquely geared toward big data analytics, Greenplum Database is powered by the world’s most advanced cost-based query optimizer delivering high analytical query performance on large data volumes.

HuggingFists is a low-code data flow tool that enables convenient use of LLM and HuggingFace models. It provides functionalities similar to Langchain, allowing users to design, debug, and manage data processing workflows, create and schedule workflow jobs, manage resources environment, and handle various data artifact resources. The tool also offers account management for users, allowing centralized management of data source accounts and API accounts. Users can access Hugging Face models through the Inference API or locally deployed models, as well as datasets on Hugging Face. HuggingFists supports breakpoint debugging, branch selection, function calls, workflow variables, and more to assist users in developing complex data processing workflows.

SoM-LLaVA is a new data source and learning paradigm for Multimodal LLMs, empowering open-source Multimodal LLMs with Set-of-Mark prompting and improved visual reasoning ability. The repository provides a new dataset that is complementary to existing training sources, enhancing multimodal LLMs with Set-of-Mark prompting and improved general capacity. By adding 30k SoM data to the visual instruction tuning stage of LLaVA, the tool achieves 1% to 6% relative improvements on all benchmarks. Users can train SoM-LLaVA via command line and utilize the implementation to annotate COCO images with SoM. Additionally, the tool can be loaded in Huggingface for further usage.

SemanticFinder is a frontend-only live semantic search tool that calculates embeddings and cosine similarity client-side using transformers.js and SOTA embedding models from Huggingface. It allows users to search through large texts like books with pre-indexed examples, customize search parameters, and offers data privacy by keeping input text in the browser. The tool can be used for basic search tasks, analyzing texts for recurring themes, and has potential integrations with various applications like wikis, chat apps, and personal history search. It also provides options for building browser extensions and future ideas for further enhancements and integrations.

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 `sec-parser` project simplifies extracting meaningful information from SEC EDGAR HTML documents by organizing them into semantic elements and a tree structure. It helps in parsing SEC filings for financial and regulatory analysis, analytics and data science, AI and machine learning, causal AI, and large language models. The tool is especially beneficial for AI, ML, and LLM applications by streamlining data pre-processing and feature extraction.

Awesome Khmer Language is a comprehensive collection of resources for the Khmer language, including tools, datasets, research papers, projects/models, blogs/slides, and miscellaneous items. It covers a wide range of topics related to Khmer language processing, such as character normalization, word segmentation, part-of-speech tagging, optical character recognition, text-to-speech, and more. The repository aims to support the development of natural language processing applications for the Khmer language by providing a diverse set of resources and tools for researchers and developers.

CoLLM is a novel method that integrates collaborative information into Large Language Models (LLMs) for recommendation. It converts recommendation data into language prompts, encodes them with both textual and collaborative information, and uses a two-step tuning method to train the model. The method incorporates user/item ID fields in prompts and employs a conventional collaborative model to generate user/item representations. CoLLM is built upon MiniGPT-4 and utilizes pretrained Vicuna weights for training.

This repository contains a collection of interview questions related to various topics such as statistics, machine learning, deep learning, Python, networking, operating systems, data structures, and algorithms. The questions cover a wide range of concepts and are suitable for individuals preparing for technical interviews in the field of artificial intelligence and data science.

Guides B2B startups in a structured customer segment evaluation process. Stop guessing! Ideate, Evaluate & Make data-driven decision.

Creates detailed, data-driven buyer personas.

Assists with biological image processing tools.

Expert in medical imaging AI, adept in machine learning tools.

A storyteller AI that draws a new illustration for every story segment.

Summarizes academic books by chapters or segments, with user prompts.

Assists with personalized, effective email marketing for e-commerce, focusing on engaging content and trends.

I assist salespeople in crafting industry-specific outreach emails.

Guides asset allocation in family segments, focusing on investments.