Best AI tools for< Deploy And Scale Applications >

Release.ai is an AI-centric platform that allows developers, operations, and leadership teams to easily deploy and manage AI applications. It offers pre-configured templates for popular open-source technologies, private AI environments for secure development, and access to GPU resources. With Release.ai, users can build, test, and scale AI solutions quickly and efficiently within their own boundaries.

Magick is a cutting-edge Artificial Intelligence Development Environment (AIDE) that empowers users to rapidly prototype and deploy advanced AI agents and applications without coding. It provides a full-stack solution for building, deploying, maintaining, and scaling AI creations. Magick's open-source, platform-agnostic nature allows for full control and flexibility, making it suitable for users of all skill levels. With its visual node-graph editors, users can code visually and create intuitively. Magick also offers powerful document processing capabilities, enabling effortless embedding and access to complex data. Its real-time and event-driven agents respond to events right in the AIDE, ensuring prompt and efficient handling of tasks. Magick's scalable deployment feature allows agents to handle any number of users, making it suitable for large-scale applications. Additionally, its multi-platform integrations with tools like Discord, Unreal Blueprints, and Google AI provide seamless connectivity and enhanced functionality.

UbiOps is an AI infrastructure platform that helps teams quickly run their AI & ML workloads as reliable and secure microservices. It offers powerful AI model serving and orchestration with unmatched simplicity, speed, and scale. UbiOps allows users to deploy models and functions in minutes, manage AI workloads from a single control plane, integrate easily with tools like PyTorch and TensorFlow, and ensure security and compliance by design. The platform supports hybrid and multi-cloud workload orchestration, rapid adaptive scaling, and modular applications with unique workflow management system.

Amazon Web Services (AWS) is a comprehensive, evolving cloud computing platform from Amazon that provides a broad set of global compute, storage, database, analytics, application, and deployment services that help organizations move faster, lower IT costs, and scale applications. With AWS, you can use as much or as little of its services as you need, and scale up or down as required with only a few minutes notice. AWS has a global network of regions and availability zones, so you can deploy your applications and data in the locations that are optimal for you.

SingleStore is a real-time data platform designed for apps, analytics, and gen AI. It offers faster hybrid vector + full-text search, fast-scaling integrations, and a free tier. SingleStore can read, write, and reason on petabyte-scale data in milliseconds. It supports streaming ingestion, high concurrency, first-class vector support, record lookups, and more.

Heroku is a cloud platform that enables developers to build, deliver, monitor, and scale applications quickly and easily. It supports multiple programming languages and provides a seamless deployment process. With Heroku, developers can focus on coding without worrying about infrastructure management.

Heroku is a cloud platform that lets companies build, deliver, monitor, and scale apps. It simplifies the process of deploying applications by providing a seamless experience for developers. With Heroku, developers can focus on writing code without worrying about infrastructure management. The platform supports various programming languages and frameworks, making it versatile for different types of applications.

Azure Static Web Apps is a platform provided by Microsoft Azure for building and deploying modern web applications. It allows developers to easily host static web content and serverless APIs with seamless integration to popular frameworks like React, Angular, and Vue. With Azure Static Web Apps, developers can quickly set up continuous integration and deployment workflows, enabling them to focus on building great user experiences without worrying about infrastructure management.

BentoML is a platform for software engineers to build, ship, and scale AI products. It provides a unified AI application framework that makes it easy to manage and version models, create service APIs, and build and run AI applications anywhere. BentoML is used by over 1000 organizations and has a global community of over 3000 members.

Cerebium is a serverless AI infrastructure platform that allows teams to build, test, and deploy AI applications quickly and efficiently. With a focus on speed, performance, and cost optimization, Cerebium offers a range of features and tools to simplify the development and deployment of AI projects. The platform ensures high reliability, security, and compliance while providing real-time logging, cost tracking, and observability tools. Cerebium also offers GPU variety and effortless autoscaling to meet the diverse needs of developers and businesses.

Allapi.ai is an advanced AI API platform designed to simplify AI integration for developers and startup founders. It offers a powerful ecosystem of models, plugins, and APIs to help users build and deploy AI-powered applications quickly and efficiently. With features like dynamic data capabilities, advanced RAG system, streamlined development process, and intelligent code assistant, Allapi.ai aims to accelerate innovation and reduce development costs. The platform provides access to cutting-edge AI models like Claude3, GPT-4, Gemini 1.5 Pro, and LLaMA 3, along with a wide range of plugins and tools to supercharge AI-driven applications.

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.

Caffe is a deep learning framework developed by Berkeley AI Research (BAIR) and community contributors. It is designed for speed, modularity, and expressiveness, allowing users to define models and optimization through configuration without hard-coding. Caffe supports both CPU and GPU training, making it suitable for research experiments and industry deployment. The framework is extensible, actively developed, and tracks the state-of-the-art in code and models. Caffe is widely used in academic research, startup prototypes, and large-scale industrial applications in vision, speech, and multimedia.

Viso Suite is a no-code computer vision platform that enables users to build, deploy, and scale computer vision applications. It provides a comprehensive set of tools for data collection, annotation, model training, application development, and deployment. Viso Suite is trusted by leading Fortune Global companies and has been used to develop a wide range of computer vision applications, including object detection, image classification, facial recognition, and anomaly detection.

AiFA Labs is an AI platform that offers a comprehensive suite of generative AI products and services for enterprises. The platform enables businesses to create, manage, and deploy generative AI applications responsibly and at scale. With a focus on governance, compliance, and security, AiFA Labs provides a range of AI tools to streamline business operations, enhance productivity, and drive innovation. From AI code assistance to chat interfaces and data synthesis, AiFA Labs empowers organizations to leverage the power of AI for various use cases across different industries.

Protect AI is a comprehensive platform designed to secure AI systems by providing visibility and manageability to detect and mitigate unique AI security threats. The platform empowers organizations to embrace a security-first approach to AI, offering solutions for AI Security Posture Management, ML model security enforcement, AI/ML supply chain vulnerability database, LLM security monitoring, and observability. Protect AI aims to safeguard AI applications and ML systems from potential vulnerabilities, enabling users to build, adopt, and deploy AI models confidently and at scale.

Restack is a developer tool and cloud infrastructure platform that enables users to build, launch, and scale AI products quickly and efficiently. With Restack, developers can go from local development to production in seconds, leveraging a variety of languages and frameworks. The platform offers templates, repository connections, and Dockerfile customization for seamless deployment. Restack Cloud provides cost-efficient scaling and GitHub integration for instant deployment. The platform simplifies the complexity of building and scaling AI applications, allowing users to move from code to production faster than ever before.

Groq is a fast AI inference tool that offers GroqCloud™ Platform and GroqRack™ Cluster for developers to build and deploy AI models with ultra-low-latency inference. It provides instant intelligence for openly-available models like Llama 3.1 and is known for its speed and compatibility with other AI providers. Groq powers leading openly-available AI models and has gained recognition in the AI chip industry. The tool has received significant funding and valuation, positioning itself as a strong challenger to established players like Nvidia.

Neurelo is a cloud API platform that offers services for PostgreSQL, MongoDB, and MySQL. It provides features such as auto-generated APIs, custom query APIs with AI assistance, query observability, schema as code, and the ability to build full-stack applications in minutes. Neurelo aims to empower developers by simplifying database programming complexities and enhancing productivity. The platform leverages the power of cloud technology, APIs, and AI to offer a seamless and efficient way to build and run applications.

Leapwork is an AI-powered test automation platform that enables users to build, manage, maintain, and analyze complex data-driven testing across various applications, including AI apps. It offers a democratized testing approach with an intuitive visual interface, composable architecture, and generative AI capabilities. Leapwork supports testing of diverse application types, web, mobile, desktop applications, and APIs. It allows for scalable testing with reusable test flows that adapt to changes in the application under test. Leapwork can be deployed on the cloud or on-premises, providing full control to the users.

Sophia is an open-source TypeScript platform designed for autonomous AI agents and LLM based workflows. It aims to automate processes, review code, assist with refactorings, and support various integrations. The platform offers features like advanced autonomous agents, reasoning/planning inspired by Google's Self-Discover paper, memory and function call history, adaptive iterative planning, and more. Sophia supports multiple LLMs/services, CLI and web interface, human-in-the-loop interactions, flexible deployment options, observability with OpenTelemetry tracing, and specific agents for code editing, software engineering, and code review. It provides a flexible platform for the TypeScript community to expand and support various use cases and integrations.

The AI Enablement Stack is a curated collection of venture-backed companies, tools, and technologies that enable developers to build, deploy, and manage AI applications. It provides a structured view of the AI development ecosystem across five key layers: Agent Consumer Layer, Observability and Governance Layer, Engineering Layer, Intelligence Layer, and Infrastructure Layer. Each layer focuses on specific aspects of AI development, from end-user interaction to model training and deployment. The stack aims to help developers find the right tools for building AI applications faster and more efficiently, assist engineering leaders in making informed decisions about AI infrastructure and tooling, and help organizations understand the AI development landscape to plan technology adoption.

R2R (RAG to Riches) is a fast and efficient framework for serving high-quality Retrieval-Augmented Generation (RAG) to end users. The framework is designed with customizable pipelines and a feature-rich FastAPI implementation, enabling developers to quickly deploy and scale RAG-based applications. R2R was conceived to bridge the gap between local LLM experimentation and scalable production solutions. **R2R is to LangChain/LlamaIndex what NextJS is to React**. A JavaScript client for R2R deployments can be found here. ### Key Features * **🚀 Deploy** : Instantly launch production-ready RAG pipelines with streaming capabilities. * **🧩 Customize** : Tailor your pipeline with intuitive configuration files. * **🔌 Extend** : Enhance your pipeline with custom code integrations. * **⚖️ Autoscale** : Scale your pipeline effortlessly in the cloud using SciPhi. * **🤖 OSS** : Benefit from a framework developed by the open-source community, designed to simplify RAG deployment.

GenAIComps is an initiative aimed at building enterprise-grade Generative AI applications using a microservice architecture. It simplifies the scaling and deployment process for production, abstracting away infrastructure complexities. GenAIComps provides a suite of containerized microservices that can be assembled into a mega-service tailored for real-world Enterprise AI applications. The modular approach of microservices allows for independent development, deployment, and scaling of individual components, promoting modularity, flexibility, and scalability. The mega-service orchestrates multiple microservices to deliver comprehensive solutions, encapsulating complex business logic and workflow orchestration. The gateway serves as the interface for users to access the mega-service, providing customized access based on user requirements.

LangGraph.js is a library for building stateful, multi-actor applications with LLMs, offering benefits such as cycles, controllability, and persistence. It allows defining flows involving cycles, providing fine-grained control over application flow and state. Inspired by Pregel and Apache Beam, it includes features like loops, persistence, human-in-the-loop workflows, and streaming support. LangGraph integrates seamlessly with LangChain.js and LangSmith but can be used independently.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

FoundationaLLM is a platform designed for deploying, scaling, securing, and governing generative AI in enterprises. It allows users to create AI agents grounded in enterprise data, integrate REST APIs, experiment with large language models, centrally manage AI agents and assets, deploy scalable vectorization data pipelines, enable non-developer users to create their own AI agents, control access with role-based access controls, and harness capabilities from Azure AI and Azure OpenAI. The platform simplifies integration with enterprise data sources, provides fine-grain security controls, load balances across multiple endpoints, and is extensible to new data sources and orchestrators. FoundationaLLM addresses the need for customized copilots or AI agents that are secure, licensed, flexible, and suitable for enterprise-scale production.

A curated list of 50+ resources to help you become a Generative AI Data Scientist. This repository includes resources on building GenAI applications with Large Language Models (LLMs), and deploying LLMs and GenAI with Cloud-based solutions.

Haystack is an end-to-end LLM framework that allows you to build applications powered by LLMs, Transformer models, vector search and more. Whether you want to perform retrieval-augmented generation (RAG), document search, question answering or answer generation, Haystack can orchestrate state-of-the-art embedding models and LLMs into pipelines to build end-to-end NLP applications and solve your use case.

The 'Generative AI with JavaScript' repository is a comprehensive resource hub for JavaScript developers interested in delving into the world of Generative AI. It provides code samples, tutorials, and resources from a video series, offering best practices and tips to enhance AI skills. The repository covers the basics of generative AI, guides on building AI applications using JavaScript, from local development to deployment on Azure, and scaling AI models. It is a living repository with continuous updates, making it a valuable resource for both beginners and experienced developers looking to explore AI with JavaScript.

Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.

NeMo Framework is a generative AI framework built for researchers and pytorch developers working on large language models (LLMs), multimodal models (MM), automatic speech recognition (ASR), and text-to-speech synthesis (TTS). The primary objective of NeMo is to provide a scalable framework for researchers and developers from industry and academia to more easily implement and design new generative AI models by being able to leverage existing code and pretrained models.

Learn Agentic AI is a repository that is part of the Panaversity Certified Agentic and Robotic AI Engineer program. It covers AI-201 and AI-202 courses, providing fundamentals and advanced knowledge in Agentic AI. The repository includes video playlists, projects, and project submission guidelines for students to enhance their understanding and skills in the field of AI engineering.

A massive list including a huge amount of products and services that are completely free! ⭐ Star on GitHub • 🤝 Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL

Awesome AI Tools is a curated list of popular tools and resources for artificial intelligence enthusiasts. It includes a wide range of tools such as machine learning libraries, deep learning frameworks, data visualization tools, and natural language processing resources. Whether you are a beginner or an experienced AI practitioner, this repository aims to provide you with a comprehensive collection of tools to enhance your AI projects and research. Explore the list to discover new tools, stay updated with the latest advancements in AI technology, and find the right resources to support your AI endeavors.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

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