Best AI tools for< Complete Applications >

Formix is an AI-powered form-filling assistant that utilizes cutting-edge AI technology to fill out any PDF document or online form with ease and accuracy. It offers intelligent autofill features, data privacy, and universal compatibility with all types of online forms. Formix is ideal for job applications, e-commerce checkout optimization, and classified ad submissions, ensuring efficient and accurate form completion across various platforms.

EasyDaddy is an AI-powered tool that simplifies and automates the process of filling out online forms. With EasyDaddy, users can create a profile once and use it to fill out forms on any website, saving time and hassle. EasyDaddy's AI learns from each form submission, improving the accuracy and relevance of future responses. The tool also allows users to attach files, making it even easier to complete forms.

SiMa.ai is an AI application that offers high-performance, power-efficient, and scalable edge machine learning solutions for various industries such as automotive, industrial, healthcare, drones, and government sectors. The platform provides MLSoC™ boards, DevKit 2.0, Palette Software 1.2, and Edgematic™ for developers to accelerate complete applications and deploy AI-enabled solutions. SiMa.ai's Machine Learning System on Chip (MLSoC) enables full-pipeline implementations of real-world ML solutions, making it a trusted platform for edge AI development.

MiGuru is a platform designed to help you find your next job quickly and efficiently. Today it has a job search engine that consolidates the public offers of the Chilean market. Through the use of artificial intelligence, we learn from your answers and use information from your CV to complete your applications automatically. In addition, we support you in improving your CV through a complete personalized report with recommendations based on industry best practices, analyzed using artificial intelligence.

AI Form Fill is an AI-powered tool that revolutionizes form filling by using advanced AI models to understand context and accurately fill forms across various websites and form types. Users can save time and boost productivity by customizing the AI's behavior, choosing from multiple AI models, and enjoying a flexible pricing system. The tool offers features like AI-powered filling, one-click magic fill, customizable context, and a referral program. With applications in job applications, survey responses, content creation, and product listings, AI Form Fill streamlines various tasks and enhances user efficiency and consistency.

Awan LLM is an AI tool that offers an Unlimited Tokens, Unrestricted, and Cost-Effective LLM Inference API Platform for Power Users and Developers. It allows users to generate unlimited tokens, use LLM models without constraints, and pay per month instead of per token. The platform features an AI Assistant, AI Agents, Roleplay with AI companions, Data Processing, Code Completion, and Applications for profitable AI-powered applications.

NeuReality is an AI-centric solution designed to democratize AI adoption by providing purpose-built tools for deploying and scaling inference workflows. Their innovative AI-centric architecture combines hardware and software components to optimize performance and scalability. The platform offers a one-stop shop for AI inference, addressing barriers to AI adoption and streamlining computational processes. NeuReality's tools enable users to deploy, afford, use, and manage AI more efficiently, making AI easy and accessible for a wide range of applications.

Lexalytics is a leading provider of text analytics and natural language processing (NLP) solutions. Our platform and services help businesses transform complex text data into valuable insights and actionable intelligence. With Lexalytics, you can: * **Analyze customer feedback** to understand what your customers are saying about your products, services, and brand. * **Identify trends and patterns** in text data to make better decisions about your business. * **Automate tasks** such as document classification, entity extraction, and sentiment analysis. * **Develop custom NLP applications** to meet your specific needs.

GrantAI is an AI-powered grant writing tool designed to help organizations secure more grant funding by creating compelling grant narratives effortlessly. With GrantAI, users can access a range of services to enhance their grant writing process, including an AI grant cowriter, tailored answers, and seamless application management. The platform has already attracted over 300 organizations and generated 800+ answers, showcasing its effectiveness in simplifying the grant application process.

Encord is a complete data development platform designed for AI applications, specifically tailored for computer vision and multimodal AI teams. It offers tools to intelligently manage, clean, and curate data, streamline labeling and workflow management, and evaluate model performance. Encord aims to unlock the potential of AI for organizations by simplifying data-centric AI pipelines, enabling the building of better models and deploying high-quality production AI faster.

The website provides a platform for Full-Stack Cloud Observability with a focus on Middleware. It offers comprehensive monitoring and analysis tools for cloud-based applications, enabling users to gain insights into the performance and health of their middleware components. The platform supports real-time data collection, visualization, and alerting to help users optimize their cloud infrastructure and ensure seamless operation.

Sofy is a revolutionary no-code testing platform for mobile applications that integrates AI to streamline the testing process. It offers features such as manual and ad-hoc testing, no-code automation, AI-powered test case generation, and real device testing. Sofy helps app development teams achieve high-quality releases by simplifying test maintenance and ensuring continuous precision. With a focus on efficiency and user experience, Sofy is trusted by top industries for its all-in-one testing solution.

Vellum AI is an AI platform that supports using Microsoft Azure hosted OpenAI models. It offers tools for prompt engineering, semantic search, prompt chaining, evaluations, and monitoring. Vellum enables users to build AI systems with features like workflow automation, document analysis, fine-tuning, Q&A over documents, intent classification, summarization, vector search, chatbots, blog generation, sentiment analysis, and more. The platform is backed by top VCs and founders of well-known companies, providing a complete solution for building LLM-powered applications.

Shaip is a human-powered data processing service specializing in AI and ML models. They offer a wide range of services including data collection, annotation, de-identification, and more. Shaip provides high-quality training data for various AI applications, such as healthcare AI, conversational AI, and computer vision. With over 15 years of expertise, Shaip helps organizations unlock critical information from unstructured data, enabling them to achieve better results in their AI initiatives.

CodeConductor is a no-code AI software development platform that empowers users to build scalable, high-quality applications without the need for extensive coding. The platform streamlines the app development process, allowing users to focus on innovation and customization. With features like accelerated app development, complete customization control, intelligent feature suggestions, dynamic data modeling, and seamless CI/CD & auto-scaled hosting, CodeConductor offers a user-friendly and efficient solution for creating web and mobile applications. The platform also provides enterprise-grade security, robust deployment options, and transparent code history tracking.

Diffblue Cover is an autonomous AI-powered unit test writing tool for Java development teams. It uses next-generation autonomous AI to automate unit testing, freeing up developers to focus on more creative work. Diffblue Cover can write a complete and correct Java unit test every 2 seconds, and it is directly integrated into CI pipelines, unlike AI-powered code suggestions that require developers to check the code for bugs. Diffblue Cover is trusted by the world's leading organizations, including Goldman Sachs, and has been proven to improve quality, lower developer effort, help with code understanding, reduce risk, and increase deployment frequency.

Datacog is an AI application that offers a comprehensive solution for efficient data warehouse management, application integration, and machine learning. It enables organizations to leverage the complete capabilities of their data assets through intuitive data organization and model training features. With zero configuration, instant deployment, scalability, and real-time monitoring, Datacog simplifies model training and streamlines decision-making. Join the ranks of industry leaders who have harnessed the power of organized data and automation with Datacog.

Moveworks is an AI-powered employee support platform that automates tasks, provides self-service support, and offers a conversational interface for employees to access information and support across all their business systems. It uses natural language processing and machine learning to understand employee queries and provide relevant answers and solutions. Moveworks integrates with various business applications, including IT service management, HR, finance, sales, marketing, and engineering tools, enabling employees to automate workflows, search for knowledge, and complete tasks within their existing chat applications.

Crowdbotics is an AI-powered platform that leverages systematic code reuse to help users build applications faster and with reduced risk. The platform uses AI to improve the process of defining app requirements, link reusable code modules with app requirements, assemble code modules into a nearly complete app, and develop differentiating features. Crowdbotics aims to transform the software development lifecycle by enabling successful code reuse through its CodeOps approach.

Brandity.ai is an AI-powered brand identity tool that helps users generate complete visual identities quickly and efficiently. The tool utilizes advanced algorithms to adapt to users' brand needs and preferences, maintaining a consistent style across all brand assets. Brandity's AI-driven identity generation ensures coherence and uniqueness in brand identities, from color schemes to art styles, tailored to fit each brand's unique requirements. The tool offers a range of pricing plans suitable for individuals, SMEs, agencies, and high-conversion entities, providing flexibility and scalability in generating logo, scenes, props, and patterns. With Brandity, users can kickstart their brand identity in less than 5 minutes, saving time and ensuring a compelling brand image across various applications.

Pipecat is an open-source framework designed for building generative AI voice bots and multimodal assistants. It provides code building blocks for interacting with AI services, creating low-latency data pipelines, and transporting audio, video, and events over the Internet. Pipecat supports various AI services like speech-to-text, text-to-speech, image generation, and vision models. Users can implement new services and contribute to the framework. Pipecat aims to simplify the development of applications like personal coaches, meeting assistants, customer support bots, and more by providing a complete framework for integrating AI services.

This repository provides a sample solution for building generative AI agents using Amazon Bedrock, Amazon DynamoDB, Amazon Kendra, Amazon Lex, and LangChain. The solution creates a generative AI financial services agent capable of assisting users with account information, loan applications, and answering natural language questions. It serves as a launchpad for developers to create personalized conversational agents for applications like chatbots and virtual assistants.

This is a development tutorial for eBPF based on CO-RE (Compile Once, Run Everywhere). It provides practical eBPF development practices from beginner to advanced, including basic concepts, code examples, and real-world applications. The tutorial focuses on eBPF examples in observability, networking, security, and more. It aims to help eBPF application developers quickly grasp eBPF development methods and techniques through examples in languages such as C, Go, and Rust. The tutorial is structured with independent eBPF tool examples in each directory, covering topics like kprobes, fentry, opensnoop, uprobe, sigsnoop, execsnoop, exitsnoop, runqlat, hardirqs, and more. The project is based on libbpf and frameworks like libbpf, Cilium, libbpf-rs, and eunomia-bpf for development.

ReductStore is a high-performance time series database designed for storing and managing large amounts of unstructured blob data. It offers features such as real-time querying, batching data, and HTTP(S) API for edge computing, computer vision, and IoT applications. The database ensures data integrity, implements retention policies, and provides efficient data access, making it a cost-effective solution for applications requiring unstructured data storage and access at specific time intervals.

A curated list of Generative AI projects, tools, artworks, and models

GPT-All-Star is an AI-powered code generation tool designed for scratch development of web applications with team collaboration of autonomous AI agents. The primary focus of this research project is to explore the potential of autonomous AI agents in software development. Users can organize their team, choose leaders for each step, create action plans, and work together to complete tasks. The tool supports various endpoints like OpenAI, Azure, and Anthropic, and provides functionalities for project management, code generation, and team collaboration.

last_layer is a security library designed to protect LLM applications from prompt injection attacks, jailbreaks, and exploits. It acts as a robust filtering layer to scrutinize prompts before they are processed by LLMs, ensuring that only safe and appropriate content is allowed through. The tool offers ultra-fast scanning with low latency, privacy-focused operation without tracking or network calls, compatibility with serverless platforms, advanced threat detection mechanisms, and regular updates to adapt to evolving security challenges. It significantly reduces the risk of prompt-based attacks and exploits but cannot guarantee complete protection against all possible threats.

The Hume AI Python SDK allows users to integrate Hume APIs directly into their Python applications. Users can access complete documentation, quickstart guides, and example notebooks to get started. The SDK is designed to provide support for Hume's expressive communication platform built on scientific research. Users are encouraged to create an account at beta.hume.ai and stay updated on changes through Discord. The SDK may undergo breaking changes to improve tooling and ensure reliable releases in the future.

Palico AI is a tech stack designed for rapid iteration of LLM applications. It allows users to preview changes instantly, improve performance through experiments, debug issues with logs and tracing, deploy applications behind a REST API, and manage applications with a UI control panel. Users have complete flexibility in building their applications with Palico, integrating with various tools and libraries. The tool enables users to swap models, prompts, and logic easily using AppConfig. It also facilitates performance improvement through experiments and provides options for deploying applications to cloud providers or using managed hosting. Contributions to the project are welcomed, with easy ways to get involved by picking issues labeled as 'good first issue'.

Azure HPC On-Demand Platform (az-hop) provides an end-to-end deployment mechanism for a base HPC infrastructure on Azure. It delivers a complete HPC cluster solution ready for users to run applications, which is easy to deploy and manage for HPC administrators. az-hop leverages various Azure building blocks and can be used as-is or easily customized and extended to meet any uncovered requirements. Industry-standard tools like Terraform, Ansible, and Packer are used to provision and configure this environment, which contains: - An HPC OnDemand Portal for all user access, remote shell access, remote visualization access, job submission, file access, and more - An Active Directory for user authentication and domain control - Open PBS or SLURM as a Job Scheduler - Dynamic resources provisioning and autoscaling is done by Azure CycleCloud pre-configured job queues and integrated health-checks to quickly avoid non-optimal nodes - A Jumpbox to provide admin access - A common shared file system for home directory and applications is delivered by Azure Netapp Files - Grafana dashboards to monitor your cluster - Remote Visualization with noVNC and GPU acceleration with VirtualGL

GeekAI is an open-source AI assistant solution based on AI large language model API, featuring a complete system with ready-to-use front-end and back-end management, providing a seamless typing experience via Websocket. It integrates various pre-trained character applications like Xiaohongshu writing assistant, English translation master, Socrates, Confucius, Steve Jobs, and weekly report assistant. The tool supports multiple large language models from platforms like OpenAI, Azure, Wenxin Yanyan, Xunfei Xinghuo, and Tsinghua ChatGLM. Additionally, it includes MidJourney and Stable Diffusion AI drawing functionalities for creating various artworks such as text-based images, face swapping, and blending images. Users can utilize personal WeChat QR codes for payment without the need for enterprise payment channels, and the tool offers integrated payment options like Alipay and WeChat Pay with support for multiple membership packages and point card purchases. It also features a plugin API for developing powerful plugins using large language model functions, including built-in plugins for Weibo hot search, today's headlines, morning news, and AI drawing functions.

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 |

CortexTheseus is a full node implementation of the Cortex blockchain, written in C++. It provides a complete set of features for interacting with the Cortex network, including the ability to create and manage accounts, send and receive transactions, and participate in consensus. CortexTheseus is designed to be scalable, secure, and easy to use, making it an ideal choice for developers building applications on the Cortex blockchain.

COMFYUI LLM PARTY is a node library designed for LLM workflow development in ComfyUI, an extremely minimalist UI interface primarily used for AI drawing and SD model-based workflows. The project aims to provide a complete set of nodes for constructing LLM workflows, enabling users to easily integrate them into existing SD workflows. It features various functionalities such as API integration, local large model integration, RAG support, code interpreters, online queries, conditional statements, looping links for large models, persona mask attachment, and tool invocations for weather lookup, time lookup, knowledge base, code execution, web search, and single-page search. Users can rapidly develop web applications using API + Streamlit and utilize LLM as a tool node. Additionally, the project includes an omnipotent interpreter node that allows the large model to perform any task, with recommendations to use the 'show_text' node for display output.

Kernel Memory (KM) is a multi-modal AI Service specialized in the efficient indexing of datasets through custom continuous data hybrid pipelines, with support for Retrieval Augmented Generation (RAG), synthetic memory, prompt engineering, and custom semantic memory processing. KM is available as a Web Service, as a Docker container, a Plugin for ChatGPT/Copilot/Semantic Kernel, and as a .NET library for embedded applications. Utilizing advanced embeddings and LLMs, the system enables Natural Language querying for obtaining answers from the indexed data, complete with citations and links to the original sources. Designed for seamless integration as a Plugin with Semantic Kernel, Microsoft Copilot and ChatGPT, Kernel Memory enhances data-driven features in applications built for most popular AI platforms.

ChatGPT-PLUS is an open-source AI assistant solution based on AI large language model API, with a built-in operational management backend for easy deployment. It integrates multiple large language models from platforms like OpenAI, Azure, ChatGLM, Xunfei Xinghuo, and Wenxin Yanyan. Additionally, it includes MidJourney and Stable Diffusion AI drawing features. The system offers a complete open-source solution with ready-to-use frontend and backend applications, providing a seamless typing experience via Websocket. It comes with various pre-trained role applications such as Xiaohongshu writer, English translation master, Socrates, Confucius, Steve Jobs, and weekly report assistant to meet various chat and application needs. Users can enjoy features like Suno Wensheng music, integration with MidJourney/Stable Diffusion AI drawing, personal WeChat QR code for payment, built-in Alipay and WeChat payment functions, support for various membership packages and point card purchases, and plugin API integration for developing powerful plugins using large language model functions.

MediaAI is a repository containing lectures and materials for Aalto University's AI for Media, Art & Design course. The course is a hands-on, project-based crash course focusing on deep learning and AI techniques for artists and designers. It covers common AI algorithms & tools, their applications in art, media, and design, and provides hands-on practice in designing, implementing, and using these tools. The course includes lectures, exercises, and a final project based on students' interests. Students can complete the course without programming by creatively utilizing existing tools like ChatGPT and DALL-E. The course emphasizes collaboration, peer-to-peer tutoring, and project-based learning. It covers topics such as text generation, image generation, optimization, and game AI.

n8n is an extendable workflow automation tool that enables you to connect anything to everything. It is open-source and can be self-hosted or used as a service. n8n provides a visual interface for creating workflows, which can be used to automate tasks such as data integration, data transformation, and data analysis. n8n also includes a library of pre-built nodes that can be used to connect to a variety of applications and services. This makes it easy to create complex workflows without having to write any code.

LinGoose is a modular Go framework designed for building AI/LLM applications. It offers the flexibility to import only the necessary modules, abstracts features for customization, and provides a comprehensive solution for developing AI/LLM applications from scratch. The framework simplifies the process of creating intelligent applications by allowing users to choose preferred implementations or create their own. LinGoose empowers developers to leverage its capabilities to streamline the development of cutting-edge AI and LLM projects.

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