Business Software for Crush

Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.

OpenAI’s mission is to ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity. We will attempt to directly build safe and beneficial AGI, but will also consider our mission fulfilled if our work aids others to achieve this outcome. Apply our API to any language task — semantic search, summarization, sentiment analysis, content generation, translation, and more — with only a few examples or by specifying your task in English. One simple integration gives you access to our constantly-improving AI technology. Explore how you integrate with the API with these sample completions.

GitHub Copilot is an AI-powered development assistant designed to accelerate software workflows from the editor to the enterprise. It works directly inside popular IDEs, terminals, and GitHub itself to help developers write, understand, and improve code faster. Copilot supports multiple leading large language models, allowing users to optimize for speed, accuracy, or cost. Developers can use Copilot to complete code, explain concepts, propose edits, and validate files in real time. It also enables agent-based workflows where Copilot can autonomously handle issues, write code, and create pull requests. With seamless integration across tools, Copilot keeps developers focused without breaking their flow. GitHub Copilot is built to scale from individual developers to large organizations with enterprise-grade controls.

Claude is a next-generation AI assistant developed by Anthropic to help individuals and teams solve complex problems with safety, accuracy, and reliability at its core. It is designed to support a wide range of tasks, including writing, editing, coding, data analysis, and research. Claude allows users to create and iterate on documents, websites, graphics, and code directly within chat using collaborative tools like Artifacts. The platform supports file uploads, image analysis, and data visualization to enhance productivity and understanding. Claude is available across web, iOS, and Android, making it accessible wherever work happens. With built-in web search and extended reasoning capabilities, Claude helps users find information and think through challenging problems more effectively. Anthropic emphasizes security, privacy, and responsible AI development to ensure Claude can be trusted in professional and personal workflows.

FreeBSD offers advanced networking, performance, security and compatibility features today which are still missing in other operating systems, even some of the best commercial ones. FreeBSD makes an ideal Internet or Intranet server. It provides robust network services under the heaviest loads and uses memory efficiently to maintain good response times for thousands of simultaneous user processes. FreeBSD brings advanced network operating system features to appliance and embedded platforms, from higher-end Intel-based appliances to ARM, PowerPC, and MIPS hardware platforms. From mail and web appliances to routers, time servers, and wireless access points, vendors around the world rely on FreeBSD’s integrated build and cross-build environments and advanced features as the foundation for their embedded products. And the Berkeley open source license lets them decide how many of their local changes they want to contribute back.

NetBSD is a free, fast, secure, and highly portable Unix-like Open Source operating system. It is available for a wide range of platforms, from large-scale servers and powerful desktop systems to handheld and embedded devices. NetBSD was originally released in 1993. Over time, its code has found its way into many surprising environments, on the basis of a long history of quality, cleanliness, and stability. The NetBSD code was originally derived from 4.4BSD Lite2 from the University of California, Berkeley. NetBSD is an entirely free and open-source UNIX-like operating system developed by an international community. It isn't a "distribution" or variant but has evolved over several decades to be a complete and unique operating system in the BSD family. NetBSD users enjoy a simple, well-documented, and fully integrated UNIX-like system that feels minimal, and in many ways traditional, while including many modern and interesting features, and support for recent hardware.

OpenBSD is developed entirely by volunteers. The project's development environment and developer events are funded through contributions collected by The OpenBSD Foundation. Contributions ensure that OpenBSD will remain a vibrant and free operating system. Hence the OpenBSD project has embedded cryptography into numerous places in the operating system. We require that the cryptographic software we use be freely available and with good licenses. We do not directly use cryptography with nasty patents. We also require that such software is from countries with useful export licenses because we do not wish to break the laws of any country. Be as politics-free as possible; solutions should be decided on the basis of technical merit.

With a strong ecosystem of tools and APIs on major cloud providers, it is easier than ever to build services with Go. With popular open source packages and a robust standard library, use Go to create fast and elegant CLIs. With enhanced memory performance and support for several IDEs, Go powers fast and scalable web applications. With fast build times, lean syntax, an automatic formatter and doc generator, Go is built to support both DevOps and SRE. Everything there is to know about Go. Get started on a new project or brush up for your existing Go code. An interactive introduction to Go in three sections. Each section concludes with a few exercises so you can practice what you've learned. The Playground allows anyone with a web browser to write Go code that we immediately compile, link, and run on our servers.

Ollama is an innovative platform that focuses on providing AI-powered tools and services, designed to make it easier for users to interact with and build AI-driven applications. Run AI models locally. By offering a range of solutions, including natural language processing models and customizable AI features, Ollama empowers developers, businesses, and organizations to integrate advanced machine learning technologies into their workflows. With an emphasis on usability and accessibility, Ollama strives to simplify the process of working with AI, making it an appealing option for those looking to harness the potential of artificial intelligence in their projects.

Model Context Protocol (MCP) is an open protocol designed to standardize how applications provide context to large language models (LLMs). It acts as a universal connector, similar to a USB-C port, allowing LLMs to seamlessly integrate with various data sources and tools. MCP supports a client-server architecture, enabling programs (clients) to interact with lightweight servers that expose specific capabilities. With growing pre-built integrations and flexibility to switch between LLM vendors, MCP helps users build complex workflows and AI agents while ensuring secure data management within their infrastructure.

The Max Plan from Anthropic's Claude platform is designed for users who require extended access and higher usage limits for their AI-powered collaboration. Ideal for frequent and demanding tasks, the Max Plan offers up to 20 times higher usage than the standard Pro plan. With flexible usage levels, users can select the plan that fits their needs—whether they need additional usage for complex data, large documents, or extended conversations. The Max Plan also includes priority access to new features and models, ensuring users always have the latest tools at their disposal.

OpenSpec is an open-source spec-driven development framework designed to bring structure and clarity to AI-assisted coding workflows. It introduces a lightweight specification layer that helps teams define requirements before writing code. The platform organizes each change into structured artifacts such as proposals, specifications, designs, and task lists. It integrates with over 20 AI coding tools, allowing developers to use their preferred assistants while maintaining consistency. OpenSpec emphasizes an iterative and flexible approach rather than rigid development phases. Its command-based workflow enables users to propose, implement, and archive features efficiently. Overall, OpenSpec helps developers align with AI systems, reduce ambiguity, and produce more predictable and reliable outcomes.

PowerShell is a cross-platform task automation and configuration management framework, consisting of a command-line shell and scripting language. Unlike most shells, which accept and return text, PowerShell is built on top of the .NET Common Language Runtime (CLR), and accepts and returns .NET objects. This fundamental change brings entirely new tools and methods for automation. Unlike traditional command-line interfaces, PowerShell cmdlets are designed to deal with objects. An object is structured information that is more than just the string of characters appearing on the screen. Command output always carries extra information that you can use if you need it. If you've used text-processing tools to process data in the past, you'll find that they behave differently when used in PowerShell. In most cases, you don't need text-processing tools to extract specific information. You directly access portions of the data using standard PowerShell object syntax.

JSON (JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language Standard ECMA-262 3rd Edition - December 1999. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. These properties make JSON an ideal data-interchange language. JSON is built on two structures: 1. A collection of name/value pairs. In various languages, this is realized as an object, record, struct, dictionary, hash table, keyed list, or associative array. 2. An ordered list of values. In most languages, this is realized as an array, vector, list, or sequence. These are universal data structures. Virtually all modern programming languages support them in one form or another.

Z.ai DevPack (GLM Coding Plan) is a subscription-based AI coding platform designed to integrate high-performance language models into existing development tools, enabling a faster, more intelligent, and stable coding workflow. It provides access to advanced models such as GLM-4.7 and GLM-5, which can be used across popular AI coding environments like Claude Code, Cline, OpenCode, and other tools that support OpenAI-compatible APIs. The system allows developers to use natural language programming to describe requirements and automatically generate code, debug issues, and execute tasks, while also offering real-time, context-aware code completion to improve productivity. It includes intelligent debugging and repair capabilities, enabling models to analyze errors, suggest fixes, and maintain smooth execution throughout development. DevPack is designed with a structured interface that AI agents can understand, allowing seamless interaction between tools and models.

Focus on your core app and get to market faster. OAuth.io handles identity infrastructure, maintenance, and security overhead, so your team doesn’t have to. Identity can be difficult, OAuth.io makes it easy. Choose identity providers, add custom attributes, customize your login page or use our widget, integrate with your app - identity solved in minutes. Manage your users from our easy to use dashboard - find and manage users, reset passwords, enforce two-factor authentication, and add memberships and permissions through OAuth.io's simple and easy to use User Management. Fully-featured, hyper-secure user authentication using passwords or tokens. From multi-tenant to complex permissions, OAuth.io has your user authorization modeling covered. Force a second factor of user authentication with our popular integrations.

Amazon Bedrock is a fully managed service that simplifies building and scaling generative AI applications by providing access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can experiment with these models, customize them using techniques like fine-tuning and Retrieval Augmented Generation (RAG), and create agents that interact with enterprise systems and data sources. As a serverless platform, Amazon Bedrock eliminates the need for infrastructure management, allowing seamless integration of generative AI capabilities into applications with a focus on security, privacy, and responsible AI practices.

Use models through the in-app Chat UI or an OpenAI-compatible local server. Minimum requirements: M1/M2/M3 Mac, or a Windows PC with a processor that supports AVX2. Linux is available in beta. One of the main reasons for using a local LLM is privacy, and LM Studio is designed for that. Your data remains private and local to your machine. You can use LLMs you load within LM Studio via an API server running on localhost.