Best AI tools for< Manage Use Cases >

AnnounceKit is an AI-powered announcement app and software designed to help companies effectively communicate product updates and news to their customers. It enables businesses to increase feature adoption, build customer trust, and engage with users through eye-catching notifications and widgets. With features like integrations, audience segmentation, customer feedback collection, and AI writing assistant, AnnounceKit offers a comprehensive solution for managing product announcements and updates.

Bubble is a visual programming platform that allows users to create web applications without the need for traditional coding. Users can design and build interactive web applications using a drag-and-drop interface, making it accessible to those without extensive coding knowledge. Bubble offers a range of features and tools to help users bring their ideas to life, from data management to user testing. With Bubble, users can prototype, build, and launch web applications quickly and efficiently.

MacWhisper is a native macOS application that utilizes OpenAI's Whisper technology for transcribing audio files into text. It offers a user-friendly interface for recording, transcribing, and editing audio, making it suitable for various use cases such as transcribing meetings, lectures, interviews, and podcasts. The application is designed to protect user privacy by performing all transcriptions locally on the device, ensuring that no data leaves the user's machine.

Kodora AI is a leading AI technology and advisory firm based in Australia, specializing in providing end-to-end AI services. They offer AI strategy development, use case identification, workforce AI training, and more. With a team of expert AI engineers and consultants, Kodora focuses on delivering practical outcomes for clients across various industries. The firm is known for its deep expertise, solution-focused approach, and commitment to driving AI adoption and innovation.

Enzai is an AI governance platform designed to help businesses navigate and comply with AI regulations and standards. It offers solutions for model risk management, generative AI, and EU AI Act compliance. Enzai provides assessments, policies, AI registry, and governance overview features to ensure AI systems' compliance and efficiency. The platform is easy to set up, efficient to use, and supported by leading AI experts. Enzai aims to be a one-stop-shop for AI governance needs, offering tailored solutions for various use cases and industries.

Locale is an AI-powered platform that enables businesses to automate their business processes using AI agents. It allows users to build AI workflows for various business functions such as marketing, sales, payments, and operations. With features like AI workflow builder, drag-and-drop and SQL builders, and integrations with popular tools like Slack and Zendesk, Locale helps in streamlining processes and increasing team productivity. The platform offers advanced features like AI Copilot, drag-&-drop Workflow Builder, SQL for complex Use Cases, and Human-in-the-loop Steps to enhance automation capabilities. Locale has been successfully used by companies to optimize workflows, reduce manual effort, and improve operational efficiency.

Absorb Software Inc. offers Absorb LMS, an AI-powered learning management system designed to deliver impactful eLearning experiences. The platform provides personalized learning paths, integrates AI for enhanced search results, and offers features like smart administration, learner engagement, eCommerce, reporting & analytics, and observation checklist. Absorb LMS caters to various use cases such as compliance training, onboarding, employee development, customer education, partner enablement, and selling courses. The platform is known for its user-friendly interface, scalability, and exceptional customer service.

Basis Theory is a platform that helps businesses build a fully programmable vault for creating engaging commerce flows, connecting with partners, managing compliance effortlessly, and maintaining control over payments data. It offers flexible payment solutions, industry-tailored payment flows, and custom payment strategies for various use cases. The platform is designed to cater to high-risk merchants, subscription platforms, marketplaces, fintechs, and more, providing full control over customer card data and tailored payment experiences.

LetHub is an AI-powered leasing automation and scheduling tool designed for property management use cases. It streamlines property management operations for multi-family operators, optimizing multifamily management with self-tour enabled features. LetHub offers a robust scheduling engine, AI chatbot capabilities, and automation for capturing leads, nurturing prospects, and converting them into tenants. The tool enhances security with bank-level safety measures and provides features like automatic tour scheduling, two-way calendar sync, open house scheduling, lockbox integration, and more. LetHub aims to revolutionize property management by combining AI automation with a human touch, making the leasing process efficient and stress-free for property managers and tenants alike.

Modulos is a Responsible AI Platform that integrates risk management, data science, legal compliance, and governance principles to ensure responsible innovation and adherence to industry standards. It offers a comprehensive solution for organizations to effectively manage AI risks and regulations, streamline AI governance, and achieve relevant certifications faster. With a focus on compliance by design, Modulos helps organizations implement robust AI governance frameworks, execute real use cases, and integrate essential governance and compliance checks throughout the AI life cycle.

vHive is an autonomous digital twin software that enables users to create a digitized portfolio of global enterprise assets. The platform offers advanced AI analytics and insights to maximize revenue and facilitate exponential growth. With vHive, users can improve operational efficiency, rapidly digitize assets worldwide, ensure security and compliance, and scale their asset portfolio through end-to-end automation. Trusted by leading enterprises, vHive provides a user-friendly platform for collecting data and insights across various use cases, ultimately driving organizational efficiency and innovation.

Docyt is an AI bookkeeping software designed for multiple businesses, offering a comprehensive platform for end-to-end bookkeeping automation. It includes features such as ExpenseFlow for expense management, RevFlow for revenue reconciliation, ClosingFlow for month-end closing, and InsightFlow for real-time financial reporting. The platform caters to various industries like accounting firms, hospitality, retail, and franchise management, providing industry-specific solutions and use cases. Docyt's AI capabilities streamline accounting workflows, enhance efficiency, and deliver accurate financial insights for business growth.

aitoolslist.io is a comprehensive platform that offers a curated list of the best AI tools categorized and ranked based on various use cases. The website provides a community-driven space for AI enthusiasts to discover trending AI tools, business ideas, tips, and news across different social media platforms. Users can explore a wide range of AI tools for tasks such as copywriting, image generation, paraphrasing, text-to-speech, audio editing, SEO, design, avatar creation, logo generation, email assistance, human resources, social media management, general writing, video editing, productivity enhancement, fun experiments, code assistance, audio editing, customer support, text-to-speech, email assistance, and more.

Spreadsheet.com is an online spreadsheet that allows users to build no-code solutions for project management, CRM, and other tasks. It offers features such as sheet views, Gantt charts, Kanban boards, form views, calendar views, attachments, related rows, charts, reports, dashboards, automations, integrations, and Spreadsheet AI. Spreadsheet.com also provides a variety of templates for specific use cases, such as project management, sales and CRM, product development, finance and accounting, lists and checklists, HR and recruiting, small business, personal, team collaboration, marketing, IT and support, construction, education, real estate, startups, and nonprofits.

Disco AI is an AI-powered social learning platform that aims to supercharge social learning experiences. It offers a comprehensive set of features including cohort-based learning, AI co-pilot, Slack integration, learning products, automations, insights & analytics, custom branding, and advanced integrations. The platform caters to various use cases such as accelerators, incubators, cohort-based learning, virtual academies, membership communities, certification programs, upskilling programs, and professional associations. Disco AI empowers users to deliver transformative learning experiences, engage with community members, and drive revenue growth through personalized and scalable AI tools.

The Notion Automation Hub is a website that provides pre-built Notion automations and databases to help users save time and improve their productivity. The website offers a variety of automations for different use cases, including job roles, workflows, and tasks. Users can also find pre-built database templates, Notion expert resources, and automation tools. The website is not affiliated with Notion Labs Inc.

Tray.ai is an AI-ready iPaaS (Integration Platform as a Service) that empowers businesses to seamlessly integrate and automate AI technologies. It offers a composable platform for building intelligent agents, delivering microservices, and ensuring scalability and governance. With Tray.ai, users can accelerate integration and automation delivery, infuse AI into business processes, and leverage AI data integration securely. The platform enables various use cases such as automating IT onboarding, lead management, embedded integrations, support agents, and order-to-cash processes.

Bench is an AI tool designed to automate hardware documentation for Hardware Engineers. It helps users document less and create more by utilizing AI for documentation writing, management, and discoverability. The tool offers features such as adapting to specific use cases, AI documentation writing, single source of truth, data-rich asset pages, highlighting compliance gaps, automated reports, and physical asset logging. Bench is advantageous for increasing productivity, improving documentation accuracy, streamlining workflows, enhancing compliance, and enabling seamless integrations. However, it may have limitations in customization options, initial learning curve, and potential dependency on AI accuracy. The tool is suitable for Hardware Engineers, Technical Writers, Documentation Specialists, Compliance Officers, and Quality Assurance Engineers. Users can find Bench using keywords like AI documentation, hardware documentation automation, AI writing tool, documentation management tool, and asset logging AI. Tasks users can perform with Bench include automate documentation, manage assets, write AI documentation, generate reports, and log physical assets.

Capacity is an AI-powered platform that offers a wide range of tools and solutions to enhance customer support, contact center operations, and overall business productivity. It leverages artificial intelligence to automate various tasks, such as speech recognition, chatbots, voice biometrics, CRM automation, and more. Capacity aims to streamline workflows, improve customer interactions, and boost efficiency by providing intelligent solutions for various industries and use cases.

Replica Studios is an AI tool that provides cutting-edge text-to-speech and speech-to-speech solutions in multiple languages for creative professionals. It offers fully licensed AI models safe for commercial use, allowing users to customize voices for various creative and professional use cases, such as gaming, animation, film, audiobooks, e-learning, and social media. The tool enables users to generate voice overs and dialogue instantly, manage scripts, and create unique voices using Voice Lab. Replica Studios prioritizes ethical voice AI by collaborating with voice actors and ensuring commercial use compliance.

Extractor is an AI-powered data extraction library for Laravel that leverages OpenAI's capabilities to effortlessly extract structured data from various sources, including images, PDFs, and emails. It features a convenient wrapper around OpenAI Chat and Completion endpoints, supports multiple input formats, includes a flexible Field Extractor for arbitrary data extraction, and integrates with Textract for OCR functionality. Extractor utilizes JSON Mode from the latest GPT-3.5 and GPT-4 models, providing accurate and efficient data extraction.

SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.

Dravid (DRD) is an advanced, AI-powered CLI coding framework designed to follow user instructions until the job is completed, including fixing errors. It can generate code, fix errors, handle image queries, manage file operations, integrate with external APIs, and provide a development server with error handling. Dravid is extensible and requires Python 3.7+ and CLAUDE_API_KEY. Users can interact with Dravid through CLI commands for various tasks like creating projects, asking questions, generating content, handling metadata, and file-specific queries. It supports use cases like Next.js project development, working with existing projects, exploring new languages, Ruby on Rails project development, and Python project development. Dravid's project structure includes directories for source code, CLI modules, API interaction, utility functions, AI prompt templates, metadata management, and tests. Contributions are welcome, and development setup involves cloning the repository, installing dependencies with Poetry, setting up environment variables, and using Dravid for project enhancements.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

The Generative AI Application Builder on AWS (GAAB) is a solution that provides a web-based management dashboard for deploying customizable Generative AI (Gen AI) use cases. Users can experiment with and compare different combinations of Large Language Model (LLM) use cases, configure and optimize their use cases, and integrate them into their applications for production. The solution is targeted at novice to experienced users who want to experiment and productionize different Gen AI use cases. It uses LangChain open-source software to configure connections to Large Language Models (LLMs) for various use cases, with the ability to deploy chat use cases that allow querying over users' enterprise data in a chatbot-style User Interface (UI) and support custom end-user implementations through an API.

ClearML Server is a backend service infrastructure for ClearML, facilitating collaboration and experiment management. It includes a web app, RESTful API, and file server for storing images and models. Users can deploy ClearML Server using Docker, AWS EC2 AMI, or Kubernetes. The system design supports single IP or sub-domain configurations with specific open ports. ClearML-Agent Services container allows launching long-lasting jobs and various use cases like auto-scaler service, controllers, optimizer, and applications. Advanced functionality includes web login authentication and non-responsive experiments watchdog. Upgrading ClearML Server involves stopping containers, backing up data, downloading the latest docker-compose.yml file, configuring ClearML-Agent Services, and spinning up docker containers. Community support is available through ClearML FAQ, Stack Overflow, GitHub issues, and email contact.

Azure OpenAI demos is a repository showcasing various demos and use cases of Azure OpenAI services. It includes demos for tasks such as image comparisons, car damage copilot, video to checklist generation, automatic data visualization, text analytics, and more. The repository provides a wide range of examples on how to leverage Azure OpenAI for different applications and industries.

The Gnosis Safe - CSV Airdrop is a Safe App designed to simplify the process of sending multiple token transfers to various recipients with different values in a single Ethereum transaction. Users can upload a CSV transfer file containing receiver addresses, token addresses, and transfer amounts. The app eliminates the need for multiple transactions and signature thresholds, streamlining the airdrop process. It also supports native token transfers and provides a user-friendly interface for initiating transactions. Developers can customize and deploy the app for specific use cases.

AIStore is a lightweight object storage system designed for AI applications. It is highly scalable, reliable, and easy to use. AIStore can be deployed on any commodity hardware, and it can be used to store and manage large datasets for deep learning and other AI applications.

The W3C Cognitive AI Community Group focuses on advancing Cognitive AI through collaboration on defining use cases, open source implementations, and application areas. The group aims to demonstrate the potential of Cognitive AI in various domains such as customer services, healthcare, cybersecurity, online learning, autonomous vehicles, manufacturing, and web search. They work on formal specifications for chunk data and rules, plausible knowledge notation, and neural networks for human-like AI. The group positions Cognitive AI as a combination of symbolic and statistical approaches inspired by human thought processes. They address research challenges including mimicry, emotional intelligence, natural language processing, and common sense reasoning. The long-term goal is to develop cognitive agents that are knowledgeable, creative, collaborative, empathic, and multilingual, capable of continual learning and self-awareness.

Log10 is a one-line Python integration to manage your LLM data. It helps you log both closed and open-source LLM calls, compare and identify the best models and prompts, store feedback for fine-tuning, collect performance metrics such as latency and usage, and perform analytics and monitor compliance for LLM powered applications. Log10 offers various integration methods, including a python LLM library wrapper, the Log10 LLM abstraction, and callbacks, to facilitate its use in both existing production environments and new projects. Pick the one that works best for you. Log10 also provides a copilot that can help you with suggestions on how to optimize your prompt, and a feedback feature that allows you to add feedback to your completions. Additionally, Log10 provides prompt provenance, session tracking and call stack functionality to help debug prompt chains. With Log10, you can use your data and feedback from users to fine-tune custom models with RLHF, and build and deploy more reliable, accurate and efficient self-hosted models. Log10 also supports collaboration, allowing you to create flexible groups to share and collaborate over all of the above features.

This repository contains notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage generative AI workflows using Generative AI on Google Cloud, powered by Vertex AI. For more Vertex AI samples, please visit the Vertex AI samples Github repository.

db-ally is a library for creating natural language interfaces to data sources. It allows developers to outline specific use cases for a large language model (LLM) to handle, detailing the desired data format and the possible operations to fetch this data. db-ally effectively shields the complexity of the underlying data source from the model, presenting only the essential information needed for solving the specific use cases. Instead of generating arbitrary SQL, the model is asked to generate responses in a simplified query language.

OpenMeter is a real-time and scalable usage metering tool for AI, usage-based billing, infrastructure, and IoT use cases. It provides a REST API for integrations and offers client SDKs in Node.js, Python, Go, and Web. OpenMeter is licensed under the Apache 2.0 License.

DagsHub is a platform for machine learning and data science teams to build, manage, and collaborate on their projects. With DagsHub you can: 1. Version code, data, and models in one place. Use the free provided DagsHub storage or connect it to your cloud storage 2. Track Experiments using Git, DVC or MLflow, to provide a fully reproducible environment 3. Visualize pipelines, data, and notebooks in and interactive, diff-able, and dynamic way 4. Label your data directly on the platform using Label Studio 5. Share your work with your team members 6. Stream and upload your data in an intuitive and easy way, while preserving versioning and structure. DagsHub is built firmly around open, standard formats for your project. In particular: * Git * DVC * MLflow * Label Studio * Standard data formats like YAML, JSON, CSV Therefore, you can work with DagsHub regardless of your chosen programming language or frameworks.

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.

LangChain Extract is a simple web server that allows you to extract information from text and files using LLMs. It is built using FastAPI, LangChain, and Postgresql. The backend closely follows the extraction use-case documentation and provides a reference implementation of an app that helps to do extraction over data using LLMs. This repository is meant to be a starting point for building your own extraction application which may have slightly different requirements or use cases.

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.

The `unstructured` library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more. The use cases of `unstructured` revolve around streamlining and optimizing the data processing workflow for LLMs. `unstructured` modular functions and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and efficient in transforming unstructured data into structured outputs.

PyLLMCore is a light-weighted interface with Large Language Models with native support for llama.cpp, OpenAI API, and Azure deployments. It offers a Pythonic API that is simple to use, with structures provided by the standard library dataclasses module. The high-level API includes the assistants module for easy swapping between models. PyLLMCore supports various models including those compatible with llama.cpp, OpenAI, and Azure APIs. It covers use cases such as parsing, summarizing, question answering, hallucinations reduction, context size management, and tokenizing. The tool allows users to interact with language models for tasks like parsing text, summarizing content, answering questions, reducing hallucinations, managing context size, and tokenizing text.

This GPT can generate software use cases, which are based on a use case templates repository and conform to a style guide.

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