Best AI tools for< Classify Leads >

Charm is an AI-powered spreadsheet assistant that helps users clean messy data, create content, summarize feedback, classify sales leads, and generate dummy data. It is a Google Sheets add-on that automates tasks that are impossible to do with traditional formulas. Charm is used by hundreds of analysts, marketers, product managers, and more.

Bot Butcher is an AI-powered antispam API for websites that helps web developers combat contact form spam bots using artificial intelligence. It offers a modern alternative to reCAPTCHA, maximizing privacy by classifying messages as spam or not spam with a large language model. The tool is designed for enterprise scalability, vertical SaaS, and website builder apps, providing continuous model improvements and context-aware classification while focusing on privacy.

JobtitlesAI is a machine-learning API that sorts job titles into two categories: field (sales, finance, I.T...) and position (executive, management, assistant...). It can be used in spreadsheets, Hubspot, or via API. JobtitlesAI is multilingual and GDPR compliant.

NLTK (Natural Language Toolkit) is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. Thanks to a hands-on guide introducing programming fundamentals alongside topics in computational linguistics, plus comprehensive API documentation, NLTK is suitable for linguists, engineers, students, educators, researchers, and industry users alike.

Cogitotech is an AI tool that specializes in data annotation and labeling expertise. The platform offers a comprehensive suite of services tailored to meet training data needs for computer vision models and AI applications. With a decade-long industry exposure, Cogitotech provides high-quality training data for industries like healthcare, financial services, security, and more. The platform helps minimize biases in AI algorithms and ensures accurate and reliable training data solutions for deploying AI in real-life systems.

Paige is a leading AI company revolutionizing pathology with next-generation technology. They provide diagnostic and biomarker AI, predictive analytics technology, and AI-assisted applications to support cancer detection, subtyping, and molecular biomarker discovery from tissue samples. Paige offers a range of AI suites for prostate, breast, colon, and PanCancer, as well as the innovative Paige Alba™ multi-modal co-pilot. Their advanced AI technology and services help streamline AI development, optimize existing applications, and drive groundbreaking advancements in cancer care.

Jekka is an AI-powered platform that helps businesses automate their workflows and processes. It offers a range of features, including natural language processing, machine learning, and computer vision, that can be used to create custom AI solutions. Jekka is designed to be easy to use, even for those with no prior experience with AI. It provides a drag-and-drop interface that makes it simple to create and deploy AI models.

Explosion is a software company specializing in developer tools and tailored solutions for AI, Machine Learning, and Natural Language Processing (NLP). They are the makers of spaCy, one of the leading open-source libraries for advanced NLP. The company offers consulting services and builds developer tools for various AI-related tasks, such as coreference resolution, dependency parsing, image classification, named entity recognition, and more.

Cohere is a leading provider of artificial intelligence (AI) tools and services. Our mission is to make AI accessible and useful to everyone, from individual developers to large enterprises. We offer a range of AI tools and services, including natural language processing, computer vision, and machine learning. Our tools are used by businesses of all sizes to improve customer service, automate tasks, and gain insights from data.

Neuwo is a leading contextual AI engine for content classification and automated tagging. It advocates that organizations of any size should have access to cutting-edge yet cost-effective contextual AI technology for meaningful automated content categorization and customization. The platform enables users to transition seamlessly from Oracle Grapeshot to Neuwo, offering advanced AI-driven algorithms for more precise targeting and increased engagement. Neuwo's technology ensures reaching the right audience at the right time, without the need for contracts. The platform enriches valuable data through intelligent content processing, brand safety, and suitability, and content activation, adding value to digital properties and businesses.

Trezy Classifier is a powerful API designed for transaction enrichment, categorization, and company identification. It offers global coverage, 350+ categories, VAT estimation, and more. The API goes beyond simple categorization to provide enriched data for each transaction, making it easy to relate to ledger accounts. With features like supplier intelligence, VAT estimation, and simple integration, Trezy Classifier empowers users to gain real profitability insights from their transactions.

Pointly is an intelligent, cloud-based B2B software solution that enables efficient automatic and advanced manual classification in 3D point clouds. It offers innovative AI techniques for fast and precise data classification and vectorization, transforming point cloud analysis into an enjoyable and efficient workflow. Pointly provides standard and custom classifiers, tools for classification and vectorization, API and on-premise classification options, collaboration features, secure cloud processing, and scalability for handling large-scale point cloud data.

Taylor is a deterministic AI tool that empowers Business & Engineering teams to enhance and automate text data processing at scale. It allows users to classify, extract, and enrich freeform text with high impact and ease of use. Taylor provides total control over customization, integration with various platforms, and the ability to drive business impact from day one by leveraging powerful machine learning capabilities.

FranzAI LLM Playground is an AI-powered tool that helps you extract, classify, and analyze unstructured text data. It leverages transformer models to provide accurate and meaningful results, enabling you to build data applications faster and more efficiently. With FranzAI, you can accelerate product and content classification, enhance data interpretation, and advance data extraction processes, unlocking key insights from your textual data.

Eigen Technologies is an AI-powered data extraction platform designed for business users to automate the extraction of data from various documents. The platform offers solutions for intelligent document processing and automation, enabling users to streamline business processes, make informed decisions, and achieve significant efficiency gains. Eigen's platform is purpose-built to deliver real ROI by reducing manual processes, improving data accuracy, and accelerating decision-making across industries such as corporates, banks, financial services, insurance, law, and manufacturing. With features like generative insights, table extraction, pre-processing hub, and model governance, Eigen empowers users to automate data extraction workflows efficiently. The platform is known for its unmatched accuracy, speed, and capability, providing customers with a flexible and scalable solution that integrates seamlessly with existing systems.

Nightfall AI is a comprehensive data security platform that leverages AI technology to provide advanced data protection solutions. The platform offers features such as data loss prevention, data protection, and data privacy for AI applications. Nightfall AI helps organizations prevent secrets sprawl, data exfiltration, and safeguard personal information across various industries. With a focus on compliance and security, Nightfall AI enables secure AI usage and encrypts sensitive data automatically. The platform is designed to eliminate blind spots in data security and offers a better way to scan, detect, and remediate data risks effectively.

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Roboflow is a platform that provides tools for building and deploying computer vision models. It offers a range of features, including data annotation, model training, and deployment. Roboflow is used by over 250,000 engineers to create datasets, train models, and deploy to production.

Hive AI provides a suite of AI models and solutions for understanding, searching, and generating content. Their AI models can be integrated into applications via APIs, enabling developers to add advanced content understanding capabilities to their products. Hive AI's solutions are used by businesses in various industries, including digital platforms, sports, media, and marketing, to streamline content moderation, automate image search and authentication, measure sponsorships, and monetize ad inventory.

Predibase is a platform for fine-tuning and serving Large Language Models (LLMs). It provides a cost-effective and efficient way to train and deploy LLMs for a variety of tasks, including classification, information extraction, customer sentiment analysis, customer support, code generation, and named entity recognition. Predibase is built on proven open-source technology, including LoRAX, Ludwig, and Horovod.

Model2Vec is a technique to turn any sentence transformer into a really small static model, reducing model size by 15x and making the models up to 500x faster, with a small drop in performance. It outperforms other static embedding models like GLoVe and BPEmb, is lightweight with only `numpy` as a major dependency, offers fast inference, dataset-free distillation, and is integrated into Sentence Transformers, txtai, and Chonkie. Model2Vec creates powerful models by passing a vocabulary through a sentence transformer model, reducing dimensionality using PCA, and weighting embeddings using zipf weighting. Users can distill their own models or use pre-trained models from the HuggingFace hub. Evaluation can be done using the provided evaluation package. Model2Vec is licensed under MIT.

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.

Obsei is an open-source, low-code, AI powered automation tool that consists of an Observer to collect unstructured data from various sources, an Analyzer to analyze the collected data with various AI tasks, and an Informer to send analyzed data to various destinations. The tool is suitable for scheduled jobs or serverless applications as all Observers can store their state in databases. Obsei is still in alpha stage, so caution is advised when using it in production. The tool can be used for social listening, alerting/notification, automatic customer issue creation, extraction of deeper insights from feedbacks, market research, dataset creation for various AI tasks, and more based on creativity.

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.

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

Awesome AI Tools is a curated list of popular tools and resources for artificial intelligence enthusiasts. It includes a wide range of tools such as machine learning libraries, deep learning frameworks, data visualization tools, and natural language processing resources. Whether you are a beginner or an experienced AI practitioner, this repository aims to provide you with a comprehensive collection of tools to enhance your AI projects and research. Explore the list to discover new tools, stay updated with the latest advancements in AI technology, and find the right resources to support your AI endeavors.

BAML is a config file format for declaring LLM functions that you can then use in TypeScript or Python. With BAML you can Classify or Extract any structured data using Anthropic, OpenAI or local models (using Ollama) ## Resources  [Discord Community](https://discord.gg/boundaryml)  [Follow us on Twitter](https://twitter.com/boundaryml) * Discord Office Hours - Come ask us anything! We hold office hours most days (9am - 12pm PST). * Documentation - Learn BAML * Documentation - BAML Syntax Reference * Documentation - Prompt engineering tips * Boundary Studio - Observability and more #### Starter projects * BAML + NextJS 14 * BAML + FastAPI + Streaming ## Motivation Calling LLMs in your code is frustrating: * your code uses types everywhere: classes, enums, and arrays * but LLMs speak English, not types BAML makes calling LLMs easy by taking a type-first approach that lives fully in your codebase: 1. Define what your LLM output type is in a .baml file, with rich syntax to describe any field (even enum values) 2. Declare your prompt in the .baml config using those types 3. Add additional LLM config like retries or redundancy 4. Transpile the .baml files to a callable Python or TS function with a type-safe interface. (VSCode extension does this for you automatically). We were inspired by similar patterns for type safety: protobuf and OpenAPI for RPCs, Prisma and SQLAlchemy for databases. BAML guarantees type safety for LLMs and comes with tools to give you a great developer experience:  Jump to BAML code or how Flexible Parsing works without additional LLM calls. | BAML Tooling | Capabilities | | ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | BAML Compiler install | Transpiles BAML code to a native Python / Typescript library (you only need it for development, never for releases) Works on Mac, Windows, Linux  | | VSCode Extension install | Syntax highlighting for BAML files Real-time prompt preview Testing UI | | Boundary Studio open (not open source) | Type-safe observability Labeling |

ZipPy is a research repository focused on fast AI detection using compression techniques. It aims to provide a faster approximation for AI detection that is embeddable and scalable. The tool uses LZMA and zlib compression ratios to indirectly measure the perplexity of a text, allowing for the detection of low-perplexity text. By seeding a compression stream with AI-generated text and comparing the compression ratio of the seed data with the sample appended, ZipPy can identify similarities in word choice and structure to classify text as AI or human-generated.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Invariant Analyzer is an open-source scanner designed for LLM-based AI agents to find bugs, vulnerabilities, and security threats. It scans agent execution traces to identify issues like looping behavior, data leaks, prompt injections, and unsafe code execution. The tool offers a library of built-in checkers, an expressive policy language, data flow analysis, real-time monitoring, and extensible architecture for custom checkers. It helps developers debug AI agents, scan for security violations, and prevent security issues and data breaches during runtime. The analyzer leverages deep contextual understanding and a purpose-built rule matching engine for security policy enforcement.

AITom is an open-source platform for AI-driven cellular electron cryo-tomography analysis. It is developed to process large amounts of Cryo-ET data, reconstruct, detect, classify, recover, and spatially model different cellular components using state-of-the-art machine learning approaches. The platform aims to automate cellular structure discovery and provide new insights into molecular biology and medical applications.

Strict JSON is a framework designed to handle JSON outputs with complex structures, fixing issues that standard json.loads() cannot resolve. It provides functionalities for parsing LLM outputs into dictionaries, supporting various data types, type forcing, and error correction. The tool allows easy integration with OpenAI JSON Mode and offers community support through tutorials and discussions. Users can download the package via pip, set up API keys, and import functions for usage. The tool works by extracting JSON values using regex, matching output values to literals, and ensuring all JSON fields are output by LLM with optional type checking. It also supports LLM-based checks for type enforcement and error correction loops.

This repository provides a curated list of open-source projects that implement instruction-tuned large language models (LLMs) with reinforcement learning from human feedback (RLHF). The projects are evaluated in terms of their openness across a predefined set of criteria in the areas of Availability, Documentation, and Access. The goal of this repository is to promote transparency and accountability in the development and deployment of LLMs.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

Just upload a numerical dataset for classification task, will apply data analysis and machine learning steps to make a best model possible.

GPT used to classify prompts as valid inputs or injection attempts. Json output.

NACE (Nomenclature of Economic Activities) is the European statistical classification of economic activities. This is not an official product. Official information here: https://nacev2.com/en

Import Export Compliance | Tariff Classification | Shipping Queries | Logistics & Supply Chain Solutions

Expert in LAStools with in-depth command line knowledge.

GICS is a classification standard developed by MSCI and S&P Dow Jones Indices. This GPT is not a MSCI and S&P product. Official website : https://www.msci.com/our-solutions/indexes/gics

Expert in UNSPSC Codes (United Nations Standard Products and Services Code®).

Expert in IATA DGR for Transportation of Dangerous Goods.

Assists with DGL coding, focusing on edge classification and link prediction.

Classifies articles into knowledge domains. source code: https://homun.posetmage.com/Agents/

Super astronomer identifying clouds in English and Chinese, sharing facts in Chinese.

What would you say if I told you there is an app on the market that can tell you if you have a hot dog or not a hot dog.

Direct answers on Lie groups for the knowledgeable.

A bilingual porcelain classification assistant.

Medical Device Expert on MDR 2017/745, IVDR 2017/746 and related MDCG guidance

Assists in identifying wildlife.

I guide on optimizing Korean sentences for embeddings.

guess the era of the image!

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

Analize uploaded files and assists in tasks based on their content.