Best AI tools for< Build Infrastructure >

The Center for AI Safety (CAIS) is a research and field-building nonprofit organization based in San Francisco. They conduct impactful research, advocacy projects, and provide resources to reduce societal-scale risks associated with artificial intelligence (AI). CAIS focuses on technical AI safety research, field-building projects, and offers a compute cluster for AI/ML safety projects. They aim to develop and use AI safely to benefit society, addressing inherent risks and advocating for safety standards.

Qubinets is a cloud data environment solutions platform that provides building blocks for building big data, AI, web, and mobile environments. It is an open-source, no lock-in, secured, and private platform that can be used on any cloud, including AWS, Digital Ocean, Google Cloud, and Microsoft Azure. Qubinets makes it easy to plan, build, and run data environments, and it streamlines and saves time and money by reducing the grunt work in setup and provisioning.

Goptimise is a no-code AI-powered scalable backend builder that helps developers craft scalable, seamless, powerful, and intuitive backend solutions. It offers a solid foundation with robust and scalable infrastructure, including dedicated infrastructure, security, and scalability. Goptimise simplifies software rollouts with one-click deployment, automating the process and amplifying productivity. It also provides smart API suggestions, leveraging AI algorithms to offer intelligent recommendations for API design and accelerating development with automated recommendations tailored to each project. Goptimise's intuitive visual interface and effortless integration make it easy to use, and its customizable workspaces allow for dynamic data management and a personalized development experience.

Global Nodes is a global leader in innovative solutions, specializing in Artificial Intelligence, Data Engineering, Cloud Services, Software Development, and Mobile App Development. They integrate advanced AI to accelerate product development and provide custom, secure, and scalable solutions. With a focus on cutting-edge technology and visionary thinking, Global Nodes offers services ranging from ideation and design to precision execution, transforming concepts into market-ready products. Their team has extensive experience in delivering top-notch AI, cloud, and data engineering services, making them a trusted partner for businesses worldwide.

Infrabase.ai is a directory of AI infrastructure products that helps users discover and explore a wide range of tools for building world-class AI products. The platform offers a comprehensive directory of products in categories such as Vector databases, Prompt engineering, Observability & Analytics, Inference APIs, Frameworks & Stacks, Fine-tuning, Audio, and Agents. Users can find tools for tasks like data storage, model development, performance monitoring, and more, making it a valuable resource for AI projects.

Outspeed is a platform for Realtime Voice and Video AI applications, providing networking and inference infrastructure to build fast, real-time voice and video AI apps. It offers tools for intelligence across industries, including Voice AI, Streaming Avatars, Visual Intelligence, Meeting Copilot, and the ability to build custom multimodal AI solutions. Outspeed is designed by engineers from Google and MIT, offering robust streaming infrastructure, low-latency inference, instant deployment, and enterprise-ready compliance with regulations such as SOC2, GDPR, and HIPAA.

Sensay is a platform that specializes in creating digital AI Replicas, offering cutting-edge cloning technology to simplify the process of developing humanlike AI Replicas. These Replicas are designed to preserve and share wisdom, catering to various needs such as dementia care, custom solutions, education, and fan engagement. Sensay ensures the creation of personalized Replicas that mimic individual personalities for realistic interactions, with a focus on continuous learning and enhancing interaction quality over time. The platform also delves into ethical and philosophical implications, emphasizing privacy protection, consent, and the exploration of identity concepts.

Granica AI is an AI data readiness platform that helps users build and manage high-quality data for AI at scale. The platform uses AI to continuously improve the AI-readiness of data, making projects faster and more impactful over time. Granica offers features such as data cost optimization, data privacy, data selection & curation, and more. Trusted by category-defining companies, Granica is recognized for its efficiency in reducing storage costs and improving data security.

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.

Cargo is a revenue operations platform that helps businesses grow their revenue by providing them with the tools they need to segment, enrich, score, and assign leads, as well as automate their revenue operations. Cargo is designed to be easy to use, even for non-technical users, and it can be integrated with a variety of other business tools. With Cargo, businesses can improve their sales performance, increase their efficiency, and make better decisions about their revenue operations.

DataRobot is a leading provider of AI cloud platforms. It offers a range of AI tools and services to help businesses build, deploy, and manage AI models. DataRobot's platform is designed to make AI accessible to businesses of all sizes, regardless of their level of AI expertise. DataRobot's platform includes a variety of features to help businesses build and deploy AI models, including: * A drag-and-drop interface that makes it easy to build AI models, even for users with no coding experience. * A library of pre-built AI models that can be used to solve common business problems. * A set of tools to help businesses monitor and manage their AI models. * A team of AI experts who can provide support and guidance to businesses using the platform.

Baseten is a machine learning infrastructure that provides a unified platform for data scientists and engineers to build, train, and deploy machine learning models. It offers a range of features to simplify the ML lifecycle, including data preparation, model training, and deployment. Baseten also provides a marketplace of pre-built models and components that can be used to accelerate the development of ML applications.

Heroku is a cloud platform that lets companies build, deliver, monitor, and scale apps. It simplifies the process of deploying applications by providing a platform as a service (PaaS) that supports various programming languages. With Heroku, developers can focus on coding without worrying about infrastructure management.

Backend.AI is an enterprise-scale cluster backend for AI frameworks that offers scalability, GPU virtualization, HPC optimization, and DGX-Ready software products. It provides a fast and efficient way to build, train, and serve AI models of any type and size, with flexible infrastructure options. Backend.AI aims to optimize backend resources, reduce costs, and simplify deployment for AI developers and researchers. The platform integrates seamlessly with existing tools and offers fractional GPU usage and pay-as-you-play model to maximize resource utilization.

Engine is an AI software engineer tool designed to help teams ship faster by connecting to various tools and building autonomously 24/7. It can complete up to 50% of tickets in minutes with no supervision, reducing backlog and workload. Engine works with established workflows, such as GitHub, Jira, Trello, Linear, and Slack, to pair program in a full-featured IDE and tackle complex problems. It allows software engineers to focus on important tasks while leaving repetitive chores to the AI.

Monterey AI is an AI-powered insights platform that helps businesses understand their customers' needs and build better products. It aggregates, triages, and analyzes user feedback, tickets, conversations, surveys, and transcripts to provide businesses with real-time insights into what their customers are saying and what they want. Monterey AI is used by businesses of all sizes, from startups to Fortune 20 companies, to improve their product development process and build better products that meet the needs of their customers.

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.

SignalWire is a cloud communications platform that provides a suite of APIs and tools for building voice, messaging, and video applications. With SignalWire, developers can quickly and easily create AI-powered applications without extensive coding. SignalWire's platform is designed to be scalable, reliable, and easy to use, making it a great choice for businesses of all sizes.

Neurochain AI is a decentralized AI-as-a-Service (DeAIAS) network that provides an innovative solution for building, launching, and using AI-powered decentralized applications (dApps). It offers a community-driven approach to AI development, incentivizing contributors with $NCN rewards. The platform aims to address challenges in the centralized AI landscape by democratizing AI development and leveraging global computing resources. Neurochain AI also features a community-powered content generation engine and is developing its own independent blockchain. The team behind Neurochain AI includes experienced professionals in infrastructure, cryptography, computer science, and AI research.

Google Cloud is a suite of cloud computing services that runs on the same infrastructure as Google. Its services include computing, storage, networking, databases, machine learning, and more. Google Cloud is designed to make it easy for businesses to develop and deploy applications in the cloud. It offers a variety of tools and services to help businesses with everything from building and deploying applications to managing their infrastructure. Google Cloud is also committed to sustainability, and it has a number of programs in place to reduce its environmental impact.

DB-GPT is an open source AI native data app development framework with AWEL(Agentic Workflow Expression Language) and agents. It aims to build infrastructure in the field of large models, through the development of multiple technical capabilities such as multi-model management (SMMF), Text2SQL effect optimization, RAG framework and optimization, Multi-Agents framework collaboration, AWEL (agent workflow orchestration), etc. Which makes large model applications with data simpler and more convenient.

SynapseML (previously known as MMLSpark) is an open-source library that simplifies the creation of massively scalable machine learning (ML) pipelines. It provides simple, composable, and distributed APIs for various machine learning tasks such as text analytics, vision, anomaly detection, and more. Built on Apache Spark, SynapseML allows seamless integration of models into existing workflows. It supports training and evaluation on single-node, multi-node, and resizable clusters, enabling scalability without resource wastage. Compatible with Python, R, Scala, Java, and .NET, SynapseML abstracts over different data sources for easy experimentation. Requires Scala 2.12, Spark 3.4+, and Python 3.8+.

sane-airscan is a SANE backend that supports driverless scanning using Apple AirScan (eSCL) and Microsoft WSD protocols. It automatically chooses between the two protocols and has been tested with various devices from Brother, Canon, Dell, Kyocera, Lexmark, Epson, HP, OKI, Panasonic, Pantum, Ricoh, Samsung, and Xerox. The backend allows for automatic and manual device discovery and configuration, supports scanning from platen and ADF in color and grayscale modes, and works with both IPv4 and IPv6. It does not require installation and does not conflict with vendor-provided proprietary software.

MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads.

KitchenAI is an open-source toolkit designed to simplify AI development by serving as an AI backend and LLMOps solution. It aims to empower developers to focus on delivering results without being bogged down by AI infrastructure complexities. With features like simplifying AI integration, providing an AI backend, and empowering developers, KitchenAI streamlines the process of turning AI experiments into production-ready APIs. It offers built-in LLMOps features, is framework-agnostic and extensible, and enables faster time-to-production. KitchenAI is suitable for application developers, AI developers & data scientists, and platform & infra engineers, allowing them to seamlessly integrate AI into apps, deploy custom AI techniques, and optimize AI services with a modular framework. The toolkit eliminates the need to build APIs and infrastructure from scratch, making it easier to deploy AI code as production-ready APIs in minutes. KitchenAI also provides observability, tracing, and evaluation tools, and offers a Docker-first deployment approach for scalability and confidence.

LLM-on-Ray is a comprehensive solution for building, customizing, and deploying Large Language Models (LLMs). It simplifies complex processes into manageable steps by leveraging the power of Ray for distributed computing. The tool supports pretraining, finetuning, and serving LLMs across various hardware setups, incorporating industry and Intel optimizations for performance. It offers modular workflows with intuitive configurations, robust fault tolerance, and scalability. Additionally, it provides an Interactive Web UI for enhanced usability, including a chatbot application for testing and refining models.

Resonance is a framework designed to facilitate interoperability and messaging between services in your infrastructure and beyond. It provides AI capabilities and takes full advantage of asynchronous PHP, built on top of Swoole. With Resonance, you can: * Chat with Open-Source LLMs: Create prompt controllers to directly answer user's prompts. LLM takes care of determining user's intention, so you can focus on taking appropriate action. * Asynchronous Where it Matters: Respond asynchronously to incoming RPC or WebSocket messages (or both combined) with little overhead. You can set up all the asynchronous features using attributes. No elaborate configuration is needed. * Simple Things Remain Simple: Writing HTTP controllers is similar to how it's done in the synchronous code. Controllers have new exciting features that take advantage of the asynchronous environment. * Consistency is Key: You can keep the same approach to writing software no matter the size of your project. There are no growing central configuration files or service dependencies registries. Every relation between code modules is local to those modules. * Promises in PHP: Resonance provides a partial implementation of Promise/A+ spec to handle various asynchronous tasks. * GraphQL Out of the Box: You can build elaborate GraphQL schemas by using just the PHP attributes. Resonance takes care of reusing SQL queries and optimizing the resources' usage. All fields can be resolved asynchronously.

The AWS Generative AI Constructs Library is an open-source extension of the AWS Cloud Development Kit (AWS CDK) that provides multi-service, well-architected patterns for quickly defining solutions in code to create predictable and repeatable infrastructure, called constructs. The goal of AWS Generative AI CDK Constructs is to help developers build generative AI solutions using pattern-based definitions for their architecture. The patterns defined in AWS Generative AI CDK Constructs are high level, multi-service abstractions of AWS CDK constructs that have default configurations based on well-architected best practices. The library is organized into logical modules using object-oriented techniques to create each architectural pattern model.

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.

Kumo search is an end-to-end search engine framework that supports full-text search, inverted index, forward index, sorting, caching, hierarchical indexing, intervention system, feature collection, offline computation, storage system, and more. It runs on the EA (Elastic automic infrastructure architecture) platform, enabling engineering automation, service governance, real-time data, service degradation, and disaster recovery across multiple data centers and clusters. The framework aims to provide a ready-to-use search engine framework to help users quickly build their own search engines. Users can write business logic in Python using the AOT compiler in the project, which generates C++ code and binary dynamic libraries for rapid iteration of the search engine.

The Oracle Cloud Infrastructure Data Science and AI services Examples repository provides demos, tutorials, and code examples showcasing various features of the OCI Data Science service and AI services. It offers tools for data scientists to develop and deploy machine learning models efficiently, with features like Accelerated Data Science SDK, distributed training, batch processing, and machine learning pipelines. Whether you're a beginner or an experienced practitioner, OCI Data Science Services provide the resources needed to build, train, and deploy models easily.

Build-your-own-AI-Assistant-Solution-Accelerator is a pre-release and preview solution that helps users create their own AI assistants. It leverages Azure Open AI Service, Azure AI Search, and Microsoft Fabric to identify, summarize, and categorize unstructured information. Users can easily find relevant articles and grants, generate grant applications, and export them as PDF or Word documents. The solution accelerator provides reusable architecture and code snippets for building AI assistants with enterprise data. It is designed for researchers looking to explore flu vaccine studies and grants to accelerate grant proposal submissions.

Director is a framework to build video agents that can reason through complex video tasks like search, editing, compilation, generation, etc. It enables users to summarize videos, search for specific moments, create clips instantly, integrate GenAI projects and APIs, add overlays, generate thumbnails, and more. Built on VideoDB's 'video-as-data' infrastructure, Director is perfect for developers, creators, and teams looking to simplify media workflows and unlock new possibilities.

24/7 Screen & Audio Capture Library to build personalized AI powered by what you've seen, said, or heard. Works with Ollama. Alternative to Rewind.ai. Open. Secure. You own your data. Rust. We are shipping daily, make suggestions, post bugs, give feedback. Building a reliable stream of audio and screenshot data, simplifying life for developers by solving non-trivial problems. Multiple installation options available. Experimental tool with various integrations and features for screen and audio capture, OCR, STT, and more. Open source project focused on enabling tooling & infrastructure for a wide range of applications.

DevOpsGPT is a revolutionary tool designed to streamline your workflow and empower you to build systems and automate tasks with ease. Tired of spending hours on repetitive DevOps tasks? DevOpsGPT is here to help! Whether you're setting up infrastructure, speeding up deployments, or tackling any other DevOps challenge, our app can make your life easier and more productive. With DevOpsGPT, you can expect faster task completion, simplified workflows, and increased efficiency. Ready to experience the DevOpsGPT difference? Visit our website, sign in or create an account, start exploring the features, and share your feedback to help us improve. DevOpsGPT will become an essential tool in your DevOps toolkit.

Pluto is a development tool dedicated to helping developers **build cloud and AI applications more conveniently** , resolving issues such as the challenging deployment of AI applications and open-source models. Developers are able to write applications in familiar programming languages like **Python and TypeScript** , **directly defining and utilizing the cloud resources necessary for the application within their code base** , such as AWS SageMaker, DynamoDB, and more. Pluto automatically deduces the infrastructure resource needs of the app through **static program analysis** and proceeds to create these resources on the specified cloud platform, **simplifying the resources creation and application deployment process**.

Weights & Biases (W&B) is a platform that helps users build better machine learning models faster by tracking and visualizing all components of the machine learning pipeline, from datasets to production models. It offers tools for tracking, debugging, evaluating, and monitoring machine learning applications. W&B provides integrations with popular frameworks like PyTorch, TensorFlow/Keras, Hugging Face Transformers, PyTorch Lightning, XGBoost, and Sci-Kit Learn. Users can easily log metrics, visualize performance, and compare experiments using W&B. The platform also supports hosting options in the cloud or on private infrastructure, making it versatile for various deployment needs.

BehaviorTree.CPP is a C++ 17 library that provides a framework to create BehaviorTrees. It was designed to be flexible, easy to use, reactive and fast. Even if our main use-case is robotics, you can use this library to build AI for games, or to replace Finite State Machines. There are few features which make BehaviorTree.CPP unique, when compared to other implementations: It makes asynchronous Actions, i.e. non-blocking, a first-class citizen. You can build reactive behaviors that execute multiple Actions concurrently (orthogonality). Trees are defined using a Domain Specific scripting language (based on XML), and can be loaded at run-time; in other words, even if written in C++, the morphology of the Trees is not hard-coded. You can statically link your custom TreeNodes or convert them into plugins and load them at run-time. It provides a type-safe and flexible mechanism to do Dataflow between Nodes of the Tree. It includes a logging/profiling infrastructure that allows the user to visualize, record, replay and analyze state transitions.

OpenOrch is a daemon that transforms servers into a powerful development environment, running AI models, containers, and microservices. It serves as a blend of Kubernetes and a language-agnostic backend framework for building applications on fixed-resource setups. Users can deploy AI models and build microservices, managing applications while retaining control over infrastructure and data.

I'm a Python and PyTorch expert with knowledge of ML infrastructure requirements ready to help you build and scale your ML projects.

Expert in CI/CD pipeline configurations and DevOps best practices.

Approachable GitLab CI/CD expert, balancing technicality with clarity.

Guides in data engineering tasks with a focus on practical solutions.

Expert in Azure's latest services, including Application Insights, API Management, and more.

Futuristic construction AI with interplanetary and nano-robotics integration

Expert in all kinds of PC builds.

街を作ろう　街を作ろう　変わらぬ鼓動　弾ませろよ (作者: @_saip_)

Guides to Build a Successful Network State

Unique custom images based on your input. Just type ideas and the brand image is created.

Your Personal Super Car Wallpaper Creator

Helps you build an OpenAI Assistant Client

Build extensions using the Eyeware Beam eye tracking SDK

Advice and guidance on how to build, maintain, and improve friendships.

Build Contents in Seconds

Business Model Canvas Creator - Build and evaluate your business model

Build your own League of Legends Style Champion with Abilities, Back Story and Splash Art

Your tech buddy helping you refurbish or build a PC from scratch, tailored to your needs, budget, and language.

Helps build full stack apps with React.

Help you build browser extensions more efficiently.