Best AI tools for< Setup Infrastructure >

ColdIQ is an AI-powered sales prospecting tool that helps B2B companies with revenue above $100k/month to build outbound systems that sell for them. The tool offers end-to-end cold outreach campaign setup and management, email infrastructure setup and warmup, audience research and targeting, data scraping and enrichment, campaigns optimization, sending automation, sales systems implementation, training on tools best practices, sales tools recommendations, free gap analysis, sales consulting, and copywriting frameworks. ColdIQ leverages AI to tailor messaging to each prospect, automate outreach, and flood calendars with opportunities.

TractoAI is an advanced AI platform that offers deep learning solutions for various industries. It provides Batch Inference with no rate limits, DeepSeek offline inference, and helps in training open source AI models. TractoAI simplifies training infrastructure setup, accelerates workflows with GPUs, and automates deployment and scaling for tasks like ML training and big data processing. The platform supports fine-tuning models, sandboxed code execution, and building custom AI models with distributed training launcher. It is developer-friendly, scalable, and efficient, offering a solution library and expert guidance for AI projects.

The website offers an AI startup builder tool that allows users to create AI applications in hours by leveraging customizable demo apps and boilerplate code. It provides a Next.js AI starter kit with various features such as full-stack web app development, styling and design with TailwindCSS, state-of-the-art AI models from OpenAI, subscriptions and payments with LemonSqueezy, and more. Users can save time on coding and infrastructure setup, focusing on building their product instead.

Mailforge is a cold email infrastructure that allows users to create hundreds of domains and mailboxes in minutes with premium deliverability and free automated setup. It is designed to help businesses send cold emails effectively and efficiently.

Paperspace is an AI tool designed to develop, train, and deploy AI models of any size and complexity. It offers a cloud GPU platform for accelerated computing, with features such as GPU cloud workflows, machine learning solutions, GPU infrastructure, virtual desktops, gaming, rendering, 3D graphics, and simulation. Paperspace provides a seamless abstraction layer for individuals and organizations to focus on building AI applications, offering low-cost GPUs with per-second billing, infrastructure abstraction, job scheduling, resource provisioning, and collaboration tools.

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.

Bemi is an Automatic Audit Trail tool designed for Postgres databases. It allows users to track data changes reliably without the need for complex engineering or costly infrastructure. Bemi offers seamless setup, contextualized data tracking, and military-grade encryption for secure data storage. It integrates with existing PostgreSQL databases, enriches low-level data changes, and provides a robust audit trail for compliance and troubleshooting purposes. Trusted by top tech companies, Bemi helps businesses streamline audit processes and focus on innovation rather than manual data tracking.

CodeSpell is an AI-powered code completion tool designed to streamline the software development life cycle (SDLC). It assists developers in generating code, documenting it, fixing errors, building APIs, automating tests, and setting up infrastructure directly within their integrated development environment (IDE). CodeSpell's unique feature, Design Studio, automates project setup by generating scaffolding, APIs, and infrastructure scripts tailored to the user's stack, reducing manual coding effort and accelerating development. The tool is compatible with popular IDEs and supports code generation in any language. CodeSpell aims to transition the software industry from AI-assisted code generation to an AI-driven landscape.

AI Bot Eye is an AI-based security system that seamlessly integrates with existing CCTV systems to deliver intelligent insights. From AI-powered Fire Detection to Real-Time Intrusion Alerts, AI Bot Eye elevates security systems with cutting-edge AI technology. The application offers features such as Intrusion Detection, Face Recognition, Fire and Smoke Detection, Speed Cam Mode, Safety Kit Detection, HeatMaps Insights, Foot Traffic Analysis, and Numberplate recognition. AI Bot Eye provides advantages like real-time alerts, enhanced security, efficient traffic monitoring, worker compliance monitoring, and optimized operational efficiency. However, the application has disadvantages such as potential false alarms, initial setup complexity, and dependency on existing CCTV infrastructure. The FAQ section addresses common queries about the application, including integration, customization, and compatibility. AI Bot Eye is suitable for jobs such as security guard, surveillance analyst, system integrator, security consultant, and safety officer. The AI keywords associated with the application include AI-based security system, CCTV integration, intrusion detection, and video analytics. Users can utilize AI Bot Eye for tasks like monitor intrusion, analyze foot traffic, detect fire, recognize faces, and manage vehicle entry.

Mito is a low-code data app infrastructure that allows users to edit spreadsheets and automatically generate Python code. It is designed to help analysts automate their repetitive Excel work and take automation into their own hands. Mito is a Jupyter extension and Streamlit component, so users don't need to set up any new infrastructure. It is easy to get started with Mito, simply install it using pip and start using it in Jupyter or Streamlit.

Evervault is a flexible payments security platform that provides maximum protection with minimum compliance burden. It allows users to easily tokenize cards, optimize margins, comply with PCI standards, avoid gateway lock-in, and set up card issuing programs. Evervault is trusted by global leaders for securing sensitive payment data and offers features like PCI compliance, payments optimization, card issuing, network tokens, key management, and more. The platform enables users to accelerate card product launches, build complex card sharing workflows, optimize payment performance, and run highly sensitive payment operations. Evervault's unique encryption model ensures data security, reduced risk of data breach, improved performance, and maximum resiliency. It offers agile payments infrastructure, customizable UI components, cross-platform support, and effortless scalability, making it a developer-friendly solution for securing payment data.

Laika AI is the world's first Web3-modeled AI ecosystem, designed and optimized for Web3 and blockchain. It offers advanced on-chain AI tools, integrating artificial intelligence and blockchain data to provide users with insights into the crypto landscape. Laika AI stands out with its user-friendly browser extension that empowers users with advanced on-chain analytics without the need for complex setups. The platform continuously learns and improves, leveraging a unique foundation and proprietary algorithms dedicated to Web3. Laika AI offers features such as DeFi research, token contract analysis, wallet insights, AI alerts, and multichain swap capabilities. It is supported by strategic partnerships with leading companies in the Web3 and Web2 space, ensuring security, high performance, and accessibility for users.

Shaped is an AI tool designed to provide relevant recommendations and search results to increase engagement, conversion, and revenue. It offers a configurable system that adapts in real-time, with features such as easy set-up, real-time adaptability, state-of-the-art model library, high customizability, and explainable results. Shaped is suitable for technical teams and offers white-glove support. It specializes in real-time ranking systems and supports multi-modal unstructured data understanding. The tool ensures secure infrastructure and has advantages like increased redemption rate, average order value, and diversity.

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.

SaaS Pronto is a revolutionary AI-powered platform that enables users to quickly build their own Software as a Service (SaaS) startups without the hassle of manual setup. By automating tasks such as database configuration, authentication, landing page design, and payment integration, SaaS Pronto empowers entrepreneurs to focus on developing profitable features. The platform offers a beginner-friendly approach, minimal coding requirements, and rapid deployment, making it ideal for indie makers and startups looking to launch MVPs efficiently and cost-effectively.

Supple.ai is an AI-powered content generation tool that helps users create high-quality written content quickly and efficiently. By leveraging advanced natural language processing algorithms, Supple.ai can generate articles, blog posts, product descriptions, and more in a matter of minutes. The tool is designed to assist content creators, marketers, and businesses in streamlining their content creation process and improving productivity.

BotGPT is a 24/7 custom AI chatbot assistant for websites. It offers a data-driven ChatGPT that allows users to create virtual assistants from their own data. Users can easily upload files or crawl their website to start asking questions and deploy a custom chatbot on their website within minutes. The platform provides a simple and efficient way to enhance customer engagement through AI-powered chatbots.

Campana is a competitive intelligence tool that helps businesses stay up-to-date on their competitors' activities. It collects and presents data on competitor websites, news, and social media in a digestible feed. Campana also uses AI to uncover insights about competitors that businesses need to know right now.

Local AI Playground is a free and open-source native app designed for AI management, verification, and inferencing. It allows users to experiment with AI offline in a private environment without the need for a GPU. The application is memory-efficient and compact, with features like CPU inferencing, model management, and digest verification. Users can start a local streaming server for AI inferencing with just two clicks. Local AI Playground aims to simplify the AI development process and provide a user-friendly platform for AI enthusiasts.

PluginLab is a platform offering a no-code User Management and Monetization solution for GPT plugins. It allows users to connect with Stripe and various OAuth Providers in just 5 minutes. The platform aims to help developers monetize their GPT plugins efficiently while providing a seamless user experience. PluginLab also offers features like authentication, monetization, real-time events monitoring, deployments, and insights generation to help users grow their business.

This repository provides a quick way for users of the SAP Business Technology Platform (BTP) to learn how to use generative AI with BTP services. It guides users through setting up the necessary infrastructure, deploying AI models, and running genAI experiments on SAP BTP. The repository includes scripts, examples, and instructions to help users get started with generative AI on the SAP BTP platform.

The Azure Open AI Application Landing Zone Solution Accelerator aims to assist in setting up development and production environments for Generative AI solutions using Azure Open AI and Azure Services. It provides deployment templates for common Gen AI solution patterns and offers customization options. The solution accelerator also offers best practices for technology usage in various scenarios.

Athina is an open-source library designed to help engineers improve the reliability and performance of Large Language Models (LLMs) through eval-driven development. It offers plug-and-play preset evals for catching and preventing bad outputs, measuring model performance, running experiments, A/B testing models, detecting regressions, and monitoring production data. Athina provides a solution to the flaws in current LLM developer workflows by offering rapid experimentation, customizable evaluators, integrated dashboard, consistent metrics, historical record tracking, and easy setup. It includes preset evaluators for RAG applications and summarization accuracy, as well as the ability to write custom evals. Athina's evals can run on both development and production environments, providing consistent metrics and removing the need for manual infrastructure setup.

The LLM Engineer's Handbook is an official repository containing a comprehensive guide on creating an end-to-end LLM-based system using best practices. It covers data collection & generation, LLM training pipeline, a simple RAG system, production-ready AWS deployment, comprehensive monitoring, and testing and evaluation framework. The repository includes detailed instructions on setting up local and cloud dependencies, project structure, installation steps, infrastructure setup, pipelines for data processing, training, and inference, as well as QA, tests, and running the project end-to-end.

The Looker GenAI Extension provides code examples and resources for building a Looker Extension that integrates with Vertex AI Large Language Models (LLMs). Users can leverage the power of LLMs to enhance data exploration and analysis within Looker. The extension offers generative explore functionality to ask natural language questions about data and generative insights on dashboards to analyze data by asking questions. It leverages components like BQML Remote Models, BQML Remote UDF with Vertex AI, and Custom Fine Tune Model for different integration options. Deployment involves setting up infrastructure with Terraform and deploying the Looker Extension by creating a Looker project, copying extension files, configuring BigQuery connection, connecting to Git, and testing the extension. Users can save example prompts and configure user settings for the extension. Development of the Looker Extension environment includes installing dependencies, starting the development server, and building for production.

AI-in-a-Box is a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction, while maintaining the highest standards of quality and efficiency. It provides essential guidance on the responsible use of AI and LLM technologies, specific security guidance for Generative AI (GenAI) applications, and best practices for scaling OpenAI applications within Azure. The available accelerators include: Azure ML Operationalization in-a-box, Edge AI in-a-box, Doc Intelligence in-a-box, Image and Video Analysis in-a-box, Cognitive Services Landing Zone in-a-box, Semantic Kernel Bot in-a-box, NLP to SQL in-a-box, Assistants API in-a-box, and Assistants API Bot in-a-box.

Build your dream team with Autogen is a repository that leverages Microsoft Autogen 0.4, Azure OpenAI, and Streamlit to create an end-to-end multi-agent application. It provides an advanced multi-agent framework based on Magentic One, with features such as a friendly UI, single-line deployment, secure code execution, managed identities, and observability & debugging tools. Users can deploy Azure resources and the app with simple commands, work locally with virtual environments, install dependencies, update configurations, and run the application. The repository also offers resources for learning more about building applications with Autogen.

The main goal of llama.cpp is to enable LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware - locally and in the cloud. It provides a Plain C/C++ implementation without any dependencies, optimized for Apple silicon via ARM NEON, Accelerate and Metal frameworks, and supports various architectures like AVX, AVX2, AVX512, and AMX. It offers integer quantization for faster inference, custom CUDA kernels for NVIDIA GPUs, Vulkan and SYCL backend support, and CPU+GPU hybrid inference. llama.cpp is the main playground for developing new features for the ggml library, supporting various models and providing tools and infrastructure for LLM deployment.

Pathway's LLM (Large Language Model) Apps provide a platform to quickly deploy AI applications using the latest knowledge from data sources. The Python application examples in this repository are Docker-ready, exposing an HTTP API to the frontend. These apps utilize the Pathway framework for data synchronization, API serving, and low-latency data processing without the need for additional infrastructure dependencies. They connect to document data sources like S3, Google Drive, and Sharepoint, offering features like real-time data syncing, easy alert setup, scalability, monitoring, security, and unification of application logic.

RAGapp is a tool designed for easy deployment of Agentic RAG in any enterprise. It allows users to configure and deploy RAG in their own cloud infrastructure using Docker. The tool is built using LlamaIndex and supports hosted AI models from OpenAI or Gemini, as well as local models using Ollama. RAGapp provides endpoints for Admin UI, Chat UI, and API, with the option to specify the model and Ollama host. The tool does not come with an authentication layer, requiring users to secure the '/admin' path in their cloud environment. Deployment can be done using Docker Compose with customizable model and Ollama host settings, or in Kubernetes for cloud infrastructure deployment. Development setup involves using Poetry for installation and building frontends.

An open-source AI assistant for taking meeting notes that captures live meeting audio, transcribes it in real-time, and generates summaries while ensuring user privacy. Perfect for teams to focus on discussions while automatically capturing and organizing meeting content without external servers or complex infrastructure. Features include modern UI, real-time audio capture, speaker diarization, local processing for privacy, and more. The tool also offers a Rust-based implementation for better performance and native integration, with features like live transcription, speaker diarization, and a rich text editor for notes. Future plans include database connection for saving meeting minutes, improving summarization quality, and adding download options for meeting transcriptions and summaries. The backend supports multiple LLM providers through a unified interface, with configurations for Anthropic, Groq, and Ollama models. System architecture includes core components like audio capture service, transcription engine, LLM orchestrator, data services, and API layer. Prerequisites for setup include Node.js, Python, FFmpeg, and Rust. Development guidelines emphasize project structure, testing, documentation, type hints, and ESLint configuration. Contributions are welcome under the MIT License.

AIBrix is an open-source initiative providing essential building blocks for scalable GenAI inference infrastructure. It delivers a cloud-native solution optimized for deploying, managing, and scaling large language model (LLM) inference, tailored to enterprise needs. Key features include High-Density LoRA Management, LLM Gateway and Routing, LLM App-Tailored Autoscaler, Unified AI Runtime, Distributed Inference, Distributed KV Cache, Cost-efficient Heterogeneous Serving, and GPU Hardware Failure Detection.

CB-Tumblebug (CB-TB) is a system for managing multi-cloud infrastructure consisting of resources from multiple cloud service providers. It provides an overview, features, and architecture. The tool supports various cloud providers and resource types, with ongoing development and localization efforts. Users can deploy a multi-cloud infra with GPUs, enjoy multiple LLMs in parallel, and utilize LLM-related scripts. The tool requires Linux, Docker, Docker Compose, and Golang for building the source. Users can run CB-TB with Docker Compose or from the Makefile, set up prerequisites, contribute to the project, and view a list of contributors. The tool is licensed under an open-source license.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

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

AIOps Modules is a collection of reusable Infrastructure as Code (IAC) modules that work with SeedFarmer CLI. The modules are decoupled and can be aggregated using GitOps principles to achieve desired use cases, removing heavy lifting for end users. They must be generic for reuse in Machine Learning and Foundation Model Operations domain, adhering to SeedFarmer Guide structure. The repository includes deployment steps, project manifests, and various modules for SageMaker, Mlflow, FMOps/LLMOps, MWAA, Step Functions, EKS, and example use cases. It also supports Industry Data Framework (IDF) and Autonomous Driving Data Framework (ADDF) Modules.

AI Exploits is a repository that showcases practical attacks against AI/Machine Learning infrastructure, aiming to raise awareness about vulnerabilities in the AI/ML ecosystem. It contains exploits and scanning templates for responsibly disclosed vulnerabilities affecting machine learning tools, including Metasploit modules, Nuclei templates, and CSRF templates. Users can use the provided Docker image to easily run the modules and templates. The repository also provides guidelines for using Metasploit modules, Nuclei templates, and CSRF templates to exploit vulnerabilities in machine learning tools.

Eternal AI is an open source AI protocol for fully onchain agents, enabling developers to create various types of onchain AI agents without middlemen. It operates on a decentralized infrastructure with state-of-the-art models and omnichain interoperability. The protocol architecture includes components like ai-kernel, decentralized-agents, decentralized-inference, decentralized-compute, agent-as-a-service, and agent-studio. Ongoing research projects include cuda-evm, nft-ai, and physical-ai. The system requires Node.js, npm, Docker Desktop, Go, and Ollama for installation. The 'eai' CLI tool allows users to create agents, fetch agent info, list agents, and chat with agents. Design principles focus on decentralization, trustlessness, production-grade quality, and unified agent interface. Featured integrations can be quickly implemented, and governance will be overseen by EAI holders in the future.

Cog is an open-source tool that lets you package machine learning models in a standard, production-ready container. You can deploy your packaged model to your own infrastructure, or to Replicate.

Answer your question about Fess

Expert in email system setup and guidance, adhering to strict rules.

Quick-setup GM GPT for space adventure TTRPG "Galactic Frontiers"

Guides on KRAs & KPIs setup

Helps you craft and setup Auto-Reply SMS message on iOS and macOS.

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Detailed email setup, then concise email crafting.

Proxy guide and setup

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Enhance D&D campaigns with Roll20 setup and custom token creation.

A ChatGPT assistant for explaining GPTs setup.

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Answers on MS server software setup and support.

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