Best AI tools for< Process Recommendation Data >

Chat Blackbox is an AI tool that specializes in AI code generation, code chat, and code search. It provides a platform where users can interact with AI to generate code, discuss code-related topics, and search for specific code snippets. The tool leverages artificial intelligence algorithms to enhance the coding experience and streamline the development process. With Chat Blackbox, users can access a wide range of features to improve their coding skills and efficiency.

ICD AI is an advanced artificial intelligence tool designed to assist healthcare professionals in accurately assigning diagnostic codes to patient records. The tool utilizes machine learning algorithms to analyze medical data and suggest appropriate ICD codes, streamlining the coding process and reducing errors. With its user-friendly interface and robust features, ICD AI is revolutionizing medical coding practices and improving efficiency in healthcare facilities.

Tootler is an AI-powered platform designed to assist students and professionals in crafting outstanding Statements of Purpose (SOPs) and letters of recommendation with minimal effort. It offers a one-stop solution for all SOP needs, including a plagiarism checker, in-built editor, autofill inputs, personal library, and affordable pricing. Tootler's AI technology generates personalized and tailored SOPs, helping users stand out in the competition. The platform is user-friendly, efficient, and revolutionizes the application process with AI-driven SOPs.

Telescope is an AI-driven lead generation platform that helps businesses find potential customers quickly and efficiently. By utilizing natural language search and next-gen search and recommendation features, Telescope allows users to generate targeted lead lists in seconds. With access to a vast global data network and advanced prospect-search capabilities, Telescope streamlines the prospecting process and provides valuable insights for sales and business development teams. The platform is designed to enhance productivity and effectiveness in lead generation activities, offering a user-friendly experience for companies of all sizes.

AI Letter Generator is a free online tool that helps users create professional letters easily with the assistance of artificial intelligence. The tool supports multiple letter types such as business letters, cover letters, personal letters, and thank you letters. It ensures privacy and data security, offers multi-language support, professional formatting options, and saves time by automating the letter creation process. Users can enjoy the core features of the AI Letter Generator for free, making it a convenient and efficient solution for letter writing needs.

Generative.ai is an AI tool designed for Salesforce consultants to enhance productivity and efficiency in creating solutions, estimates, and proposals. The tool leverages AI technology to generate detailed proposals in minutes, provide commercial insights, and recommend product features based on extensive data processing. It aims to streamline the proposal creation process and improve accuracy through AI-assisted enhancement.

Soho is a real estate platform that utilizes AI technology to match users with properties for sale and rent based on their criteria. The platform offers a personalized property search experience, market insights, and expert advice to streamline the property buying and renting process. Users can easily find properties, compare agents, track market trends, and receive property recommendations using data and machine learning. Soho aims to simplify the property search journey by providing a user-friendly platform with advanced features and a vast database of listings.

HuLoop Automation is an AI-powered platform that offers intelligent automation solutions for businesses. It provides a no-code platform for automating complex business processes, test automation, and productivity discovery. With a focus on human-in-the-loop decisioning, HuLoop aims to simplify automation implementation and make it fast and affordable for companies. The platform integrates with existing technologies, offers data-driven recommendations, and helps organizations optimize their processes for increased efficiency and productivity.

BarRaiser is an Interview Intelligence Platform designed to help companies make better hiring decisions. It offers AI-powered tools for structured interviews, interviewer training, and interview platform services. The platform aims to streamline the recruitment process by providing live interview guidance, interview quality reports, hiring recommendations, and real-time feedback. BarRaiser's AI Interview Notes feature leverages artificial intelligence to enhance recruitment processes and talent assessment. The platform is trusted by over 500 customers worldwide and has proven metrics for savings, speed, and precision in the hiring process.

Fireopps is an AI Business Plan Generator that allows users to create a professional business plan in just 2 minutes using AI technology. The platform offers a fast and efficient way to generate a comprehensive business plan, including SWOT analysis, market analysis, competitor research, ideal customer profile, and more. Fireopps aims to streamline the process of creating a business plan by leveraging AI-driven insights and data-backed recommendations.

Quickchat AI is a custom AI assistant designed to automate customer support, lead generation, and more. It allows users to design, tweak, and deploy their own AI assistant trained on their data. Quickchat AI offers a range of features including customizable AI assistant name, conversation style, knowledge and actions, and deployment options. It also provides integrations with popular tools and systems, making it easy to use AI in everyday workflows.

Find My Remote is an AI-powered job search platform that streamlines the job hunting process by leveraging artificial intelligence to find and structure job postings from various ATS platforms. Users can set their job preferences, receive personalized job matches, and save time by applying to curated job listings. The platform offers exclusive job opportunities not typically found on popular job search websites like LinkedIn. With features such as job discovery, application tracking, and faster application process, Find My Remote aims to revolutionize the way job seekers find and apply for jobs.

Owlbot is an AI-powered chatbot that integrates and interprets data from various sources. It simplifies data analysis and presents insights in a user-friendly format, allowing you to make informed decisions. Owlbot can handle large volumes of data and supports 95 languages. It can be embedded on your website or used via API. Owlbot is designed to be user-friendly and intuitive, making complex data analysis accessible to everyone, regardless of their data expertise.

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.

BuildShip.com is a powerful AI Assistant Builder that allows users to create AI Assistant ChatBots in just 5 minutes. The platform enables users to connect to tools and databases without the need for any code, offering full flexibility with low-code options. Users can build AI Assistants using popular models like OpenAI, Claude 3, and Azure, and can easily ship their creations as APIs, chat widgets, workflow, or schedule jobs. The platform also provides secure integration with databases, the ability to generate custom action nodes, and seamless plugin chat widgets for websites. BuildShip.com simplifies the process of building AI Assistants and empowers users to bring their ideas to life effortlessly.

DigitalGenius is an AI-powered customer service platform designed specifically for e-commerce businesses. It offers a range of features to help businesses automate customer interactions, resolve issues quickly and efficiently, and improve the overall customer experience. DigitalGenius seamlessly integrates with existing e-commerce platforms and shipping carriers, allowing businesses to manage customer inquiries and orders from a single platform. The platform's AI capabilities enable it to understand customer intent, generate personalized responses, and provide proactive support. DigitalGenius is trusted by leading brands such as On, Air up, and Waterdrop, and has helped them improve customer satisfaction, reduce costs, and scale their operations.

Aion Assists is a GPT-powered customer service plugin for WooCommerce stores. It offers unique features such as understanding critical typos in inputs, responding to multiple independent questions in a single output, and prioritizing and responding to customer requests in an attention-grabbing manner. With Aion Assists, businesses can enhance their customer support and interaction, leading to increased sales and improved customer satisfaction.

Clari is a revenue operations platform that helps businesses track, forecast, and analyze their revenue performance. It provides a unified view of the revenue process, from lead generation to deal closing, and helps businesses identify and address revenue leaks. Clari is powered by AI and machine learning, which helps it to automate tasks, provide insights, and make recommendations. It is used by businesses of all sizes, from startups to large enterprises.

Clari is a revenue operations platform that helps businesses track, forecast, and close deals. It provides a unified view of the sales pipeline, allowing teams to identify and address potential problems early on. Clari also uses artificial intelligence to surface insights and recommendations, helping businesses improve their sales performance.

Akadimia Ai is an AI-powered platform designed to provide users with a range of educational resources and tools. The platform leverages artificial intelligence to offer personalized learning experiences, interactive tutorials, and assessments. Users can access a variety of courses, quizzes, and study materials tailored to their individual needs and learning preferences. Akadimia Ai aims to enhance the learning process by offering adaptive content recommendations and progress tracking features. Whether you are a student looking to improve your academic performance or a professional seeking to acquire new skills, Akadimia Ai offers a comprehensive learning solution to help you achieve your goals.

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 is a collection of papers and resources related to recommendation systems, focusing on foundation models, transferable recommender systems, large language models, and multimodal recommender systems. It explores questions such as the necessity of ID embeddings, the shift from matching to generating paradigms, and the future of multimodal recommender systems. The papers cover various aspects of recommendation systems, including pretraining, user representation, dataset benchmarks, and evaluation methods. The repository aims to provide insights and advancements in the field of recommendation systems through literature reviews, surveys, and empirical studies.

This repository contains the source code for the SIGIR 2023 paper 'Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited'. It provides resources for evaluating foundation, transferable, multi-modal, and LLM recommendation models, along with datasets, pre-trained models, and training strategies for IDRec and MoRec using in-batch debiased cross-entropy loss. The repository also offers large-scale datasets, code for SASRec with in-batch debias cross-entropy loss, and information on joining the lab for research opportunities.

MicroLens is a content-driven micro-video recommendation dataset at scale. It provides a large dataset with multimodal data, including raw text, images, audio, video, and video comments, for tasks such as multi-modal recommendation, foundation model building, and fairness recommendation. The dataset is available in two versions: MicroLens-50K and MicroLens-100K, with extracted features for multimodal recommendation tasks. Researchers can access the dataset through provided links and reach out to the corresponding author for the complete dataset. The repository also includes codes for various algorithms like VideoRec, IDRec, and VIDRec, each implementing different video models and baselines.

This paper list is about Large Language Model-enhanced Recommender System. It also contains some related works. Keywords: recommendation system, large language models

NineRec is a benchmark dataset suite for evaluating transferable recommendation models. It provides datasets for pre-training and transfer learning in recommender systems, focusing on multimodal and foundation model tasks. The dataset includes user-item interactions, item texts in multiple languages, item URLs, and raw images. Researchers can use NineRec to develop more effective and efficient methods for pre-training recommendation models beyond end-to-end training. The dataset is accompanied by code for dataset preparation, training, and testing in PyTorch environment.

This repository contains a curated list of resources on generative information retrieval, including research papers, datasets, tools, and applications. Generative information retrieval is a subfield of information retrieval that uses generative models to generate new documents or passages of text that are relevant to a given query. This can be useful for a variety of tasks, such as question answering, summarization, and document generation. The resources in this repository are intended to help researchers and practitioners stay up-to-date on the latest advances in generative information retrieval.

VectorETL is a lightweight ETL framework designed to assist Data & AI engineers in processing data for AI applications quickly. It streamlines the conversion of diverse data sources into vector embeddings and storage in various vector databases. The framework supports multiple data sources, embedding models, and vector database targets, simplifying the creation and management of vector search systems for semantic search, recommendation systems, and other vector-based operations.

A curated repository of code recipes, demos, and resources for basic and advanced Redis use cases in the AI ecosystem. It includes demos for ArxivChatGuru, Redis VSS, Vertex AI & Redis, Agentic RAG, ArXiv Search, and Product Search. Recipes cover topics like Getting started with RAG, Semantic Cache, Advanced RAG, and Recommendation systems. The repository also provides integrations/tools like RedisVL, AWS Bedrock, LangChain Python, LangChain JS, LlamaIndex, Semantic Kernel, RelevanceAI, and DocArray. Additional content includes blog posts, talks, reviews, and documentation related to Vector Similarity Search, AI-Powered Document Search, Vector Databases, Real-Time Product Recommendations, and more. Benchmarks compare Redis against other Vector Databases and ANN benchmarks. Documentation includes QuickStart guides, official literature for Vector Similarity Search, Redis-py client library docs, Redis Stack documentation, and Redis client list.

Streamline Analyst is a cutting-edge, open-source application powered by Large Language Models (LLMs) designed to revolutionize data analysis. This Data Analysis Agent effortlessly automates tasks such as data cleaning, preprocessing, and complex operations like identifying target objects, partitioning test sets, and selecting the best-fit models based on your data. With Streamline Analyst, results visualization and evaluation become seamless. It aims to expedite the data analysis process, making it accessible to all, regardless of their expertise in data analysis. The tool is built to empower users to process data and achieve high-quality visualizations with unparalleled efficiency, and to execute high-performance modeling with the best strategies. Future enhancements include Natural Language Processing (NLP), neural networks, and object detection utilizing YOLO, broadening its capabilities to meet diverse data analysis needs.

**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.

Robocorp is a platform that allows users to create, deploy, and operate Python automations and AI actions. It provides an easy way to extend the capabilities of AI agents, assistants, and copilots with custom actions written in Python. Users can create and deploy tools, skills, loaders, and plugins that securely connect any AI Assistant platform to their data and applications. The Robocorp Action Server makes Python scripts compatible with ChatGPT and LangChain by automatically creating and exposing an API based on function declaration, type hints, and docstrings. It simplifies the process of developing and deploying AI actions, enabling users to interact with AI frameworks effortlessly.

Deej-A.I. is an advanced machine learning project that aims to revolutionize music recommendation systems by using artificial intelligence to analyze and recommend songs based on their content and characteristics. The project involves scraping playlists from Spotify, creating embeddings of songs, training neural networks to analyze spectrograms, and generating recommendations based on similarities in music features. Deej-A.I. offers a unique approach to music curation, focusing on the 'what' rather than the 'how' of DJing, and providing users with personalized and creative music suggestions.

allms is a versatile and powerful library designed to streamline the process of querying Large Language Models (LLMs). Developed by Allegro engineers, it simplifies working with LLM applications by providing a user-friendly interface, asynchronous querying, automatic retrying mechanism, error handling, and output parsing. It supports various LLM families hosted on different platforms like OpenAI, Google, Azure, and GCP. The library offers features for configuring endpoint credentials, batch querying with symbolic variables, and forcing structured output format. It also provides documentation, quickstart guides, and instructions for local development, testing, updating documentation, and making new releases.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

ENOVA is an open-source service for Large Language Model (LLM) deployment, monitoring, injection, and auto-scaling. It addresses challenges in deploying stable serverless LLM services on GPU clusters with auto-scaling by deconstructing the LLM service execution process and providing configuration recommendations and performance detection. Users can build and deploy LLM with few command lines, recommend optimal computing resources, experience LLM performance, observe operating status, achieve load balancing, and more. ENOVA ensures stable operation, cost-effectiveness, efficiency, and strong scalability of LLM services.

Cool-GenAI-Fashion-Papers is a curated list of resources related to GenAI-Fashion, including papers, workshops, companies, and products. It covers a wide range of topics such as fashion design synthesis, outfit recommendation, fashion knowledge extraction, trend analysis, and more. The repository provides valuable insights and resources for researchers, industry professionals, and enthusiasts interested in the intersection of AI and fashion.

SuperSonic is a next-generation BI platform that integrates Chat BI (powered by LLM) and Headless BI (powered by semantic layer) paradigms. This integration ensures that Chat BI has access to the same curated and governed semantic data models as traditional BI. Furthermore, the implementation of both paradigms benefits from the integration: * Chat BI's Text2SQL gets augmented with context-retrieval from semantic models. * Headless BI's query interface gets extended with natural language API. SuperSonic provides a Chat BI interface that empowers users to query data using natural language and visualize the results with suitable charts. To enable such experience, the only thing necessary is to build logical semantic models (definition of metric/dimension/tag, along with their meaning and relationships) through a Headless BI interface. Meanwhile, SuperSonic is designed to be extensible and composable, allowing custom implementations to be added and configured with Java SPI. The integration of Chat BI and Headless BI has the potential to enhance the Text2SQL generation in two dimensions: 1. Incorporate data semantics (such as business terms, column values, etc.) into the prompt, enabling LLM to better understand the semantics and reduce hallucination. 2. Offload the generation of advanced SQL syntax (such as join, formula, etc.) from LLM to the semantic layer to reduce complexity. With these ideas in mind, we develop SuperSonic as a practical reference implementation and use it to power our real-world products. Additionally, to facilitate further development we decide to open source SuperSonic as an extensible framework.

The Python Redis Vector Library (RedisVL) is a tailor-made client for AI applications leveraging Redis. It enhances applications with Redis' speed, flexibility, and reliability, incorporating capabilities like vector-based semantic search, full-text search, and geo-spatial search. The library bridges the gap between the emerging AI-native developer ecosystem and the capabilities of Redis by providing a lightweight, elegant, and intuitive interface. It abstracts the features of Redis into a grammar that is more aligned to the needs of today's AI/ML Engineers or Data Scientists.

Strategic advisor for triage management and pipeline optimization in business operations.

I will guide you during the process of buying a new or used car based on your requirements. Have fun and enjoy! This is version 0.1.

Detailed, step-by-step Lightroom guidance for impressive photos. Say goodbye to ambiguity, includes starting values and direct recommendations. Autonomously guides you through the editing process, demystifying photo editing and boosting your confidence.

Hello I'm Cashier I Assistant! What would you like help with today?

An AI waiter for Baci Bistro & Bar, knowledgeable about the menu and ready to assist.

Upload your process map and I will analyse and suggest improvements

Friendly process engineer for Coda.io

Guides clear BPMN process design with ASCII art

Optimizes production processes for improved efficiency and quality.

Optimizes business operations through process enhancements.

Optimizes production processes for efficient large-scale operations.

Improves operational efficiency by optimizing processes and reducing waste.

Discover Process Talks: Your Next Investment!

Optimizes manufacturing processes for efficiency and quality.

Emulating Whitehead's insights on 'Process and Reality'

Process Documentation for serving GPTs.

Trademark Process Assistant, Not an Attorney & Definitely Not Legal Advice (independently verify info received). Gain insights on U.S. trademark process & concepts, USPTO resources, application steps & more - all while being reminded of the importance of consulting legal pros 4 specific guidance.

Structured process for prioritizing marketing tasks based on strategic alignment. Outputs in Eisenhower, RACI and other methodologies.

Assists in the caregiving process for seniors.

Guides future parents through the adoption process with empathy and information.