Best AI tools for< Deploy Systems >

The Responsible AI Institute is a global non-profit organization dedicated to equipping organizations and AI professionals with tools and knowledge to create, procure, and deploy AI systems that are safe and trustworthy. They offer independent assessments, conformity assessments, and certification programs to ensure that AI systems align with internal policies, regulations, laws, and best practices for responsible technology use. The institute also provides resources, news, and a community platform for members to collaborate and stay informed about responsible AI practices and regulations.

Hopsworks is an AI platform that offers a comprehensive solution for building, deploying, and monitoring machine learning systems. It provides features such as a Feature Store, real-time ML capabilities, and generative AI solutions. Hopsworks enables users to develop and deploy reliable AI systems, orchestrate and monitor models, and personalize machine learning models with private data. The platform supports batch and real-time ML tasks, with the flexibility to deploy on-premises or in the cloud.

Compassionate AI is a cutting-edge AI-powered platform that empowers individuals and organizations to create and deploy AI solutions that are ethical, responsible, and aligned with human values. With Compassionate AI, users can access a comprehensive suite of tools and resources to design, develop, and implement AI systems that prioritize fairness, transparency, and accountability.

Tangram Vision is a company that provides sensor calibration tools and infrastructure for robotics and autonomous vehicles. Their products include MetriCal, a high-speed bundle adjustment software for precise sensor calibration, and AutoCal, an on-device, real-time calibration health check and adjustment tool. Tangram Vision also offers a high-resolution depth sensor called HiFi, which combines high-resolution depth data with high-powered AI capabilities. The company's mission is to accelerate the development and deployment of autonomous systems by providing the tools and infrastructure needed to ensure the accuracy and reliability of sensors.

Microsoft Responsible AI Toolbox is a suite of tools designed to assess, develop, and deploy AI systems in a safe, trustworthy, and ethical manner. It offers integrated tools and functionalities to help operationalize Responsible AI in practice, enabling users to make user-facing decisions faster and easier. The Responsible AI Dashboard provides a customizable experience for model debugging, decision-making, and business actions. With a focus on responsible assessment, the toolbox aims to promote ethical AI practices and transparency in AI development.

InsightFace is an open-source deep face analysis library that provides a rich variety of state-of-the-art algorithms for face recognition, detection, and alignment. It is designed to be efficient for both training and deployment, making it suitable for research institutions and industrial organizations. InsightFace has achieved top rankings in various challenges and competitions, including the ECCV 2022 WCPA Challenge, NIST-FRVT 1:1 VISA, and WIDER Face Detection Challenge 2019.

The OECD Artificial Intelligence Policy Observatory, also known as OECD.AI, is a platform that focuses on AI policy issues, risks, and accountability. It provides resources, tools, and metrics to build and deploy trustworthy AI systems. The platform aims to promote innovative and trustworthy AI through collaboration with countries, stakeholders, experts, and partners. Users can access information on AI incidents, AI principles, policy areas, publications, and videos related to AI. OECD.AI emphasizes the importance of data privacy, generative AI management, AI computing capacities, and AI's potential futures.

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.

PoplarML is a platform that enables the deployment of production-ready, scalable ML systems with minimal engineering effort. It offers one-click deploys, real-time inference, and framework agnostic support. With PoplarML, users can seamlessly deploy ML models using a CLI tool to a fleet of GPUs and invoke their models through a REST API endpoint. The platform supports Tensorflow, Pytorch, and JAX models.

Composio is an integration platform for AI Agents and LLMs that allows users to access over 150 tools with just one line of code. It offers seamless integrations, managed authentication, a repository of tools, and powerful RPA tools to streamline and optimize the connection and interaction between AI Agents/LLMs and various APIs/services. Composio simplifies JSON structures, improves variable names, and enhances error handling to increase reliability by 30%. The platform is SOC Type II compliant, ensuring maximum security of user data.

PixieBrix is an AI engagement platform that allows users to build, deploy, and manage internal AI tools to drive team productivity. It unifies AI landscapes with oversight and governance for enterprise scale. The platform is enterprise-ready and fully customizable to meet unique needs, and can be deployed on any site, making it easy to integrate into existing systems. PixieBrix leverages the power of AI and automation to harness the latest technology to streamline workflows and take productivity to new heights.

Promptmate.io is an AI-powered app builder that allows users to create customized applications based on leading AI systems. With Promptmate, users can combine different AI systems, add external data, and automate processes to streamline their workflows. The platform offers a range of features, including pre-built app templates, bulk processing, and data extenders, making it easy for users to build and deploy AI-powered applications without the need for coding.

Duckietown is a platform for delivering cutting-edge robotics and AI learning experiences. It offers teaching resources to instructors, hands-on activities to learners, an accessible research platform to researchers, and a state-of-the-art ecosystem for professional training. Duckietown's mission is to make robotics and AI education state-of-the-art, hands-on, and accessible to all.

GenWorlds is an event-based communication framework for building multi-agent systems. It offers a platform for creating Generative AI applications where users can design customizable environments, utilize scalable architecture, access a repository of memories and tools, choose cognitive processes for agents, and pick coordination protocols. GenWorlds aims to foster a vibrant community of developers, AI enthusiasts, and innovators to collaborate, innovate, share knowledge, and grow together.

SymphonyAI offers AI SaaS solutions for financial crime prevention, helping organizations detect fraud, conduct customer due diligence, and prevent payment fraud. Their solutions leverage generative and predictive AI to enhance efficiency and effectiveness in investigating financial crimes. SymphonyAI's products cater to industries like banking, insurance, financial markets, and private banking, providing rapid deployment, scalability, and seamless integration to meet regulatory compliance requirements.

Fathom5 is a company that specializes in the intersection of AI and industrial systems. They offer a range of products and services to help customers build the industrial systems of the future. Their solutions are focused on critical infrastructure, making it more resilient, flexible, and efficient.

BotX is a No-Code AI Platform that enables users to automate and deploy generative AI workflows, chatbots, and solutions. It offers production-ready AI systems to increase productivity, build AI agents and chatbots, automate workflows, create or process documents, and connect models effortlessly. With a focus on efficiency and reliability, BotX aims to simplify AI implementation for businesses of all sizes.

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.

Ambi Robotics is an AI-powered robotics company that offers solutions for parcel sortation. Their innovative technology combines hardware and software to empower people to handle more efficiently. With solutions like AmbiSort A-Series and AmbiSort B-Series, they provide AI-powered robotic small parcel sorting and modular parcel induction and sorting systems. Ambi Robotics focuses on enhancing efficiency, scaling seamlessly, and delivering customer-centered experiences. Their technology includes Sim2Real AI Robot dexterity for real-world simulation and intelligent gripper technology for precise pick-and-place capabilities. The company aims to optimize facility performance, maximize sorting accuracy, and boost efficiency with reliable uptime. Ambi Robotics is dedicated to providing solutions that are easy to deploy, powerful, and seamlessly integrate with existing workflows.

Graphlogic.ai is an AI-powered platform that offers Conversational AI solutions through text and voice bots. It provides partner-enabled services for various industries, including HR, customer support, marketing, and internal task management. The platform features AI-powered chatbots with goal-oriented NLU and rule-based bots, seamless integrations with CRM systems, and 24/7 omnichannel availability. Graphlogic.ai aims to transform and speed up customer service and FAQ conversations by providing instant replies in a human-like manner. It also offers dedicated HR manager bots, hiring assistants for mass recruitment, responsible managers for internal tasks, and outbound marketing coordinators.

Ivy is an open-source machine learning framework that enables you to: * 🔄 **Convert code into any framework** : Use and build on top of any model, library, or device by converting any code from one framework to another using `ivy.transpile`. * ⚒️ **Write framework-agnostic code** : Write your code once in `ivy` and then choose the most appropriate ML framework as the backend to leverage all the benefits and tools. Join our growing community 🌍 to connect with people using Ivy. **Let's** unify.ai **together 🦾**

Ivy is an open-source machine learning framework that enables users to convert code between different ML frameworks and write framework-agnostic code. It allows users to transpile code from one framework to another, making it easy to use building blocks from different frameworks in a single project. Ivy also serves as a flexible framework that breaks free from framework limitations, allowing users to publish code that is interoperable with various frameworks and future frameworks. Users can define trainable modules and layers using Ivy's stateful API, making it easy to build and train models across different backends.

The IBM Power Systems AIX Collection provides modules to manage configurations and deployments of Power AIX systems, enabling workloads on Power platforms as part of an enterprise automation strategy through the Ansible ecosystem. It includes example best practices, requirements for AIX versions, Ansible, and Python, along with resources for documentation and contribution.

Mojo is a new programming language that bridges the gap between research and production by combining Python syntax and ecosystem with systems programming and metaprogramming features. Mojo is still young, but it is designed to become a superset of Python over time.

AI System School is a curated list of research in machine learning systems, focusing on ML/DL infra, LLM infra, domain-specific infra, ML/LLM conferences, and general resources. It provides resources such as data processing, training systems, video systems, autoML systems, and more. The repository aims to help users navigate the landscape of AI systems and machine learning infrastructure, offering insights into conferences, surveys, books, videos, courses, and blogs related to the field.

Midori AI is a cutting-edge initiative dedicated to advancing the field of artificial intelligence through research, development, and community engagement. They focus on creating innovative AI solutions, exploring novel approaches, and empowering users to harness the power of AI. Key areas of focus include cluster-based AI, AI setup assistance, AI development for Discord bots, model serving and hosting, novel AI memory architectures, and Carly - a fully simulated human with advanced AI capabilities. They have also developed the Midori AI Subsystem to streamline AI workloads by providing simplified deployment, standardized configurations, isolation for AI systems, and a growing library of backends and tools.

The Next-Generation LLM-based Recommender Systems Survey is a comprehensive overview of the latest advancements in recommender systems leveraging Large Language Models (LLMs). The survey covers various paradigms, approaches, and applications of LLMs in recommendation tasks, including generative and non-generative models, multimodal recommendations, personalized explanations, and industrial deployment. It discusses the comparison with existing surveys, different paradigms, and specific works in the field. The survey also addresses challenges and future directions in the domain of LLM-based recommender systems.

llama_deploy is an async-first framework for deploying, scaling, and productionizing agentic multi-service systems based on workflows from llama_index. It allows building workflows in llama_index and deploying them seamlessly with minimal changes to code. The system includes services endlessly processing tasks, a control plane managing state and services, an orchestrator deciding task handling, and fault tolerance mechanisms. It is designed for high-concurrency scenarios, enabling real-time and high-throughput applications.

AIGES is a core component of the Athena Serving Framework, designed as a universal encapsulation tool for AI developers to deploy AI algorithm models and engines quickly. By integrating AIGES, you can deploy AI algorithm models and engines rapidly and host them on the Athena Serving Framework, utilizing supporting auxiliary systems for networking, distribution strategies, data processing, etc. The Athena Serving Framework aims to accelerate the cloud service of AI algorithm models and engines, providing multiple guarantees for cloud service stability through cloud-native architecture. You can efficiently and securely deploy, upgrade, scale, operate, and monitor models and engines without focusing on underlying infrastructure and service-related development, governance, and operations.

Praison AI is a low-code, centralised framework that simplifies the creation and orchestration of multi-agent systems for various LLM applications. It emphasizes ease of use, customization, and human-agent interaction. The tool leverages AutoGen and CrewAI frameworks to facilitate the development of AI-generated scripts and movie concepts. Users can easily create, run, test, and deploy agents for scriptwriting and movie concept development. Praison AI also provides options for full automatic mode and integration with OpenAI models for enhanced AI capabilities.

Nexior allows users to deploy their own AI application site in minutes, offering services like GPT, Midjourney, ChatDoc, QrArt, etc. Users can use the platform without any development experience, AI account purchases, API support concerns, or payment system configurations. It supports various features such as GPT 3.5/4.0, Midjourney modes, unlimited document uploads, artistic QR code generation, payment and referral systems, and user system support. Nexior is open source, free under the MIT license, and easy to configure and deploy.

OpenKF (Open Knowledge Flow) is an online intelligent customer service system. It is an open-source customer service system based on OpenIM, supporting LLM (Local Knowledgebase) customer service and multi-channel customer service. It is easy to integrate with third-party systems, deploy, and perform secondary development. The system provides features like login page, config page, dashboard page, platform page, and session page. Users can quickly get started with OpenKF by following the installation and run instructions. The architecture follows MVC design with a standardized directory structure. The community encourages involvement through community meetings, contributions, and development. OpenKF is licensed under the Apache 2.0 license.

The LLM Twin Course is a free, end-to-end framework for building production-ready LLM systems. It teaches you how to design, train, and deploy a production-ready LLM twin of yourself powered by LLMs, vector DBs, and LLMOps good practices. The course is split into 11 hands-on written lessons and the open-source code you can access on GitHub. You can read everything and try out the code at your own pace.

AutoGPTQ is an easy-to-use LLM quantization package with user-friendly APIs, based on GPTQ algorithm (weight-only quantization). It provides a simple and efficient way to quantize large language models (LLMs) to reduce their size and computational cost while maintaining their performance. AutoGPTQ supports a wide range of LLM models, including GPT-2, GPT-J, OPT, and BLOOM. It also supports various evaluation tasks, such as language modeling, sequence classification, and text summarization. With AutoGPTQ, users can easily quantize their LLM models and deploy them on resource-constrained devices, such as mobile phones and embedded systems.

Fortuna is a library for uncertainty quantification that enables users to estimate predictive uncertainty, assess model reliability, trigger human intervention, and deploy models safely. It provides calibration and conformal methods for pre-trained models in any framework, supports Bayesian inference methods for deep learning models written in Flax, and is designed to be intuitive and highly configurable. Users can run benchmarks and bring uncertainty to production systems with ease.

Langchain.rb is a Ruby library that makes it easy to build LLM-powered applications. It provides a unified interface to a variety of LLMs, vector search databases, and other tools, making it easy to build and deploy RAG (Retrieval Augmented Generation) systems and assistants. Langchain.rb is open source and available under the MIT License.

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

Vearch is a cloud-native distributed vector database designed for efficient similarity search of embedding vectors in AI applications. It supports hybrid search with vector search and scalar filtering, offers fast vector retrieval from millions of objects in milliseconds, and ensures scalability and reliability through replication and elastic scaling out. Users can deploy Vearch cluster on Kubernetes, add charts from the repository or locally, start with Docker-compose, or compile from source code. The tool includes components like Master for schema management, Router for RESTful API, and PartitionServer for hosting document partitions with raft-based replication. Vearch can be used for building visual search systems for indexing images and offers a Python SDK for easy installation and usage. The tool is suitable for AI developers and researchers looking for efficient vector search capabilities in their applications.

Svelte Commerce is an open-source frontend for eCommerce, utilizing a PWA and headless approach with a modern JS stack. It supports integration with various eCommerce backends like MedusaJS, Woocommerce, Bigcommerce, and Shopify. The API flexibility allows seamless connection with third-party tools such as payment gateways, POS systems, and AI services. Svelte Commerce offers essential eCommerce features, is both SSR and SPA, superfast, and free to download and modify. Users can easily deploy it on Netlify or Vercel with zero configuration. The tool provides features like headless commerce, authentication, cart & checkout, TailwindCSS styling, server-side rendering, proxy + API integration, animations, lazy loading, search functionality, faceted filters, and more.

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 |

a daily challenge

Ethics-focused GPT builder assistant based on European AI guidelines, recommendations and regulations

Expert on Jelastic/Virtuozzo PaaS solutions.

Azure Arc expert providing guidance on architecture, deployment, and management.

Senior DevOps Engineer specializing in Ansible

日本語Nutanix Bibleから回答するチャット。

Expert in Docker and Docker Swarm solutions and troubleshooting.

Expert advice on Azure, clear and concise.

Guides from Terraform install to script deployment.

Expert in V2X Technologies

AI engineering expert offering insights into machine learning and AI development.

Expert in CI/CD integration for various tools and languages.

Paranoid AI coder with a knack for sentient AI and eerie humor.

Expert software architect with experience in design, construction, development, testing and deployment of Web, Mobile and Standalone software architectures

Expert in Rust coding for ESP32, offering detailed programming and deployment guidance.

Web Deployment, Designing, 3D - Modeling, CMS system and much more Providing

Docker & cloud computing expert

BATman specializes in creating .bat and .ps1 scripts for the Win 11 OS.

A GPT Agent that connects to your server via SSH

Technical assistant specializing in Docker and Docker Compose. Lets Debug !