Best AI tools for< Consolidate Data >

Datarails is a financial planning and analysis platform for Excel users. It automates data consolidation, reporting, and planning while enabling finance teams to continue using their spreadsheets and financial models. With Datarails, finance teams can save time on repetitive tasks and focus on strategic insights that drive business growth.

GoX Data Automation Software is a cloud-based tool designed to save time with data analytics and automation. It allows users to connect to different APIs/sources, create reports with beautiful charts and graphs, automate report generation, and consolidate data from various sources into reports or dashboards. The software, known as Two Minute Reports (TMR), works seamlessly with Google Sheets and Looker Studio to help users efficiently manage their reporting tasks.

ASK BOSCO® is an AI reporting and forecasting tool designed for agencies and retailers. It connects and consolidates data for easy reporting, predicts media spend allocation, plans budgets, and forecasts future performance with 96% accuracy. The tool combines internal marketing data with algorithmic modeling to create personalized reporting dashboards, enabling data-driven marketing decisions and insights. ASK BOSCO® is trusted by leading brands and agencies, offering statistical modeling and machine learning for media budget planning and benchmarking against competitors.

Servcy is an all-in-one business management tool that helps you consolidate data from all your tools in one place. With Servcy, you can manage your communications, tasks, documents, payments, and time tracking all in one place. Servcy also uses AI to help you prioritize and respond to the most important messages, organize and manage your tasks, and get answers from your documents.

Fleak AI Workflows is a low-code serverless API Builder designed for data teams to effortlessly integrate, consolidate, and scale their data workflows. It simplifies the process of creating, connecting, and deploying workflows in minutes, offering intuitive tools to handle data transformations and integrate AI models seamlessly. Fleak enables users to publish, manage, and monitor APIs effortlessly, without the need for infrastructure requirements. It supports various data types like JSON, SQL, CSV, and Plain Text, and allows integration with large language models, databases, and modern storage technologies.

Fullpath is an AI-powered Customer Data Platform (CDP) designed specifically for auto dealerships. It helps dealers activate their data to create exceptional customer experiences through automated, AI-driven marketing campaigns. Fullpath integrates dealership-specific data sources, leverages AI technology for deep insights and personalized experiences, and ensures data security and compliance. The platform offers features like data connectivity, 360° shopper profiles, data activation, marketing automations, AI-driven insights, and sales enablement.

TextMine is an AI-powered knowledge base that helps businesses analyze, manage, and search thousands of documents. It uses AI to analyze unstructured textual data and document databases, automatically retrieving key terms to help users make informed decisions. TextMine's features include a document vault for storing and managing documents, a categorization system for organizing documents, and a data extraction tool for extracting insights from documents. TextMine can help businesses save time, money, and improve efficiency by automating manual data entry and information retrieval tasks.

TextMine is an AI-powered knowledge base designed for businesses to manage and analyze critical documents efficiently. It offers features such as document analysis, smart-search capabilities, automated data extraction, and structured dataset transformation. TextMine helps businesses save time and money by streamlining document management processes and enabling informed decision-making. The application caters to various industries like Technology, Legal Services, and Financial Services, providing solutions for teams in Procurement, Finance, Compliance, CIOs, and CDOs.

Findem is an AI Talent Acquisition Software that offers a comprehensive platform for candidate sourcing, talent CRM, talent analytics, market intelligence, and more. It leverages AI technology to automate talent acquisition workflows and consolidate top-of-funnel activities. Findem provides unique 3D data and attributes to empower organizations in transforming their talent strategy. The platform is designed to attract, nurture, and hire with confidence, offering features such as Copilot for Sourcing, external talent sourcing, inbound management, candidate rediscovery, and talent CRM.

OpenLIT is an AI application designed as an Observability tool for GenAI and LLM applications. It empowers model understanding and data visualization through an interactive Learning Interpretability Tool. With OpenTelemetry-native support, it seamlessly integrates into projects, offering features like fine-tuning performance, real-time data streaming, low latency processing, and visualizing data insights. The tool simplifies monitoring with easy installation and light/dark mode options, connecting to popular observability platforms for data export. Committed to OpenTelemetry community standards, OpenLIT provides valuable insights to enhance application performance and reliability.

Hoop is an AI task management tool designed for busy professionals to help capture and prioritize tasks across various communication tools like meetings, Slack, and email. It uses AI to intelligently capture tasks, provide summaries, and automatically label priorities, allowing users to focus on important tasks without the need for manual project management. Hoop ensures data privacy and security through encryption and visibility controls, making it a reliable tool for enhancing productivity and task organization.

Cordel Connect is an open-data inspection management platform that enables the storage, management, visualization, and intelligent analysis of railway inspection data. It offers powerful, precise, unattended sensing systems and data workflows to help railways automate high-frequency, high-precision inspections from any rail vehicle. The platform consolidates all survey and inspection data into a single source of truth, eliminating data silos and integrating with existing systems. Cordel Connect utilizes powerful AI to automate the infrastructure inspection process, delivering improved inspection insights and compliance. It also provides modules for managing surveys, asset inspections, and safety compliance assessments tailored to network standards.

Momos is a customer engagement platform designed for restaurants, offering super powered customer experience management driven by AI to build stronger relationships and drive customer loyalty. It provides unified feedback management, custom surveys for customer feedback, AI-powered automation and support, customer analytics and insights, review boosting, and customer activation tools. Momos helps multi-location brands globally manage guest feedback, collect insights, and drive sales with segmentation and outbound marketing. The platform consolidates all customer channels and feedback into one user-friendly interface, offers AI-powered automation for improved workflow, and provides in-depth customer insights for data-driven decisions and marketing goals.

Popmenu is an AI-powered marketing technology platform designed to help restaurants grow their business. It offers solutions such as website design, dynamic menu technology, online ordering, marketing automation, and AI phone answering. Popmenu aims to simplify restaurant operations, capture guest preferences, automate personalized marketing, and consolidate tools for better efficiency. With a focus on independent restaurants, quick service restaurants, hospitality groups, and full-service restaurants, Popmenu helps owners enhance customer service, improve margins, and attract more guests. The platform has received positive reviews from clients and is known for its exceptional customer service.

Bridge Legal is a transformative AI-powered platform designed for legal professionals. It offers scalable, customizable services to adapt instantly to high-volume litigation needs. The platform optimizes every facet of the legal business, providing case insight, document analysis, record review acceleration, intelligent report analytics, and essential details summarization to streamline case preparations.

This application is an AI-powered developer relations agent that can automate and consolidate manual developer support. It can automate onboarding and support for developers, and provide insights to improve documentation. The application is trained on technical developer documentation to automate repetitive questions, leading to cost savings, reduced response waiting time, and increased automation of support requests.

Re:amaze is an integrated customer service, live chat, and helpdesk platform for online businesses. It offers a range of features to help businesses provide better customer service and engagement, including a shared inbox, live chat, chatbots, push campaigns, AI-powered response and creation tools, a customizable FAQ center, a status page, and real-time customer activity monitoring. Re:amaze is designed to help businesses consolidate all their customer support channels and respond faster than ever before. It also offers a range of integrations with other business tools and applications.

Aviso is an End-to-End AI Revenue Platform that offers Conversational Intelligence and RevOps solutions. It provides a comprehensive platform for account research, planning, and revenue execution. Aviso leverages AI technology to predict and drive revenue, optimize sales performance, and prioritize go-to-market activities. The platform aims to consolidate underperforming sales apps into an integrated AI solution for accurate, prescriptive, and repeatable revenue generation.

Senseloaf Platform is an AI-powered platform designed to streamline the recruiting process by offering features such as Dynamic Matching, Conversational AI, Talent Discovery, and Resume Parser. It aims to provide a seamless and efficient experience for both recruiters and candidates, leveraging AI technology to personalize engagement, accelerate hiring productivity, and make insightful decisions. The platform offers end-to-end automation for recruiting teams, enabling them to consolidate, configure, automate, and control the recruitment process. With a focus on intelligent recruiting, Senseloaf Platform helps recruiters engage with top candidates, personalize candidate engagement, and boost hiring productivity with intelligence.

ResponseCX is an AI tool designed for Shopify brands to build autonomous AI Agents for customer support. It enables fast-growing ecommerce organizations to deploy custom AI agents in record time, providing a dedicated AI engineer to assist in the process. ResponseCX allows brands to consolidate all platforms into one place to create customized, on-brand AI Agents capable of fully autonomous ticket resolution. The tool offers features such as fast learning, fast deployment, 100% uptime, and unlimited ticket volume, leading to significant cost reductions and improved customer satisfaction.

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

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.

This repository serves as a comprehensive survey on the application of Large Language Models (LLMs) on tabular data, focusing on tasks such as prediction, data generation, and table understanding. It aims to consolidate recent progress in this field by summarizing key techniques, metrics, datasets, models, and optimization approaches. The survey identifies strengths, limitations, unexplored territories, and gaps in the existing literature, providing insights for future research directions. It also offers code and dataset references to empower readers with the necessary tools and knowledge to address challenges in this rapidly evolving domain.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

Synmetrix is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube.js to consolidate metrics from various sources and distribute them downstream via a SQL API. Use cases include data democratization, business intelligence and reporting, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

Chat with your data using OpenAI and AI Search. This solution accelerator uses an Azure OpenAI GPT model and an Azure AI Search index generated from your data, which is integrated into a web application to provide a natural language interface, including speech-to-text functionality, for search queries. Users can drag and drop files, point to storage, and take care of technical setup to transform documents. There is a web app that users can create in their own subscription with security and authentication.

moai is a PyTorch-based AI Model Development Kit (MDK) designed to improve data-driven model workflows, design, and understanding. It offers modularity via monads for model building blocks, reproducibility via configuration-based design, productivity via a data-driven domain modelling language (DML), extensibility via plugins, and understanding via inter-model performance and design aggregation. The tool provides specific integrated actions like play, train, evaluate, plot, diff, and reprod to support heavy data-driven workflows with analytics, knowledge extraction, and reproduction. moai relies on PyTorch, Lightning, Hydra, TorchServe, ONNX, Visdom, HiPlot, Kornia, Albumentations, and the wider open-source community for its functionalities.

This repository is a curated list of papers focused on the detection of Large Language Models (LLMs)-generated content. It includes the latest research papers covering detection methods, datasets, attacks, and more. The repository is regularly updated to include the most recent papers in the field.

NExT-GPT is an end-to-end multimodal large language model that can process input and generate output in various combinations of text, image, video, and audio. It leverages existing pre-trained models and diffusion models with end-to-end instruction tuning. The repository contains code, data, and model weights for NExT-GPT, allowing users to work with different modalities and perform tasks like encoding, understanding, reasoning, and generating multimodal content.

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.

This repository contains a collection of research papers related to watermarking techniques for text and images, specifically focusing on large language models (LLMs). The papers cover various aspects of watermarking LLM-generated content, including robustness, statistical understanding, topic-based watermarks, quality-detection trade-offs, dual watermarks, watermark collision, and more. Researchers have explored different methods and frameworks for watermarking LLMs to protect intellectual property, detect machine-generated text, improve generation quality, and evaluate watermarking techniques. The repository serves as a valuable resource for those interested in the field of watermarking for LLMs.

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)

Extension | OS is an open-source browser extension that brings AI directly to users' web browsers, allowing them to access powerful models like LLMs seamlessly. Users can create prompts, fix grammar, and access intelligent assistance without switching tabs. The extension aims to revolutionize online information interaction by integrating AI into everyday browsing experiences. It offers features like Prompt Factory for tailored prompts, seamless LLM model access, secure API key storage, and a Mixture of Agents feature. The extension was developed to empower users to unleash their creativity with custom prompts and enhance their browsing experience with intelligent assistance.

Flare is an open-source AI-powered decentralized social network client for Android/iOS/macOS, consolidating multiple social networks into one platform. It allows cross-posting content, ensures privacy, and plans to implement features like mixed timeline, AI-powered functions, and support for various platforms. The project is in active development and aims to provide a seamless social networking experience for users.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

Automatically prompts for and merges spreadsheets.

Upload your Excel files, then merge them!

GPT tranined Oracle PBCS manuals

Urban Analyzer with consolidated files containing just UR information.

Explains debt consolidation strategies.

Explains quick loans, their types, benefits, and risks informatively.

Advises on debt management strategies to improve financial stability.

Expert on South African debt counselling and related legal matters

Friendly credit advisor and letter drafter for disputes.