Top Muse for Small Business Alternatives

With Assembled, support leaders can unify human and AI agents in one intelligent platform that drives efficiency without compromising quality. Our technology enables over 50% automation of customer interactions, precise demand forecasting, and optimized staffing across in-house teams and BPO partners. From live workload balancing to AI agents that match your workflows and brand voice, Assembled ensures every chat, call, and email is handled with speed and consistency. Companies including Stripe, Canva, and Robinhood trust Assembled to elevate the customer experience and reduce operational costs. Core solutions span workforce and vendor management, real-time performance visibility, and AI Copilot — giving agents translation, reply suggestions, and instant task automation to resolve issues faster.

Perplexity Computer is an advanced AI super agent engineered to autonomously manage and complete complex digital tasks from initial idea to final output. Users provide a high-level description of the desired result, and the system automatically decomposes the request into structured subtasks handled by specialized AI models. It can generate fully functional websites, produce detailed analytical reports, compile structured datasets, and create image or video content within a single coordinated workflow. The platform dynamically selects the most suitable AI model for each task component, optimizing performance based on research depth, creative generation, or rapid information retrieval. Designed for sustained autonomous operation, it can execute multi-stage projects over extended periods without continuous human supervision. Its orchestration engine manages routing, task sequencing, and execution logic to ensure smooth end-to-end delivery. By abstracting away model selection and technical configuration, it transforms complex AI workflows into a simple outcome-driven experience. The interface focuses on translating user intent directly into completed work products. Integrated model switching allows the system to adapt to varying task requirements in real time. Perplexity Computer reduces the need for manual coordination between tools, prompts, and workflows. It streamlines advanced AI capabilities into a unified environment built for productivity and scalability. The result is a powerful, autonomous agent designed to turn ideas into finished digital assets efficiently and intelligently.

Claude Duet is a proactive AI assistant developed by Anthropic to automate personal productivity tasks, coordinate professional responsibilities, and complete multistep assignments across connected applications. The platform is powered by Claude Opus 5.5 and operates through a dedicated cloud computer that enables autonomous interaction with external services. Unlike traditional conversational assistants that primarily respond to user prompts, Claude Duet can proactively identify important developments and deliver personalized updates when attention or decisions are required. Its morning briefing functionality reviews relevant emails, calendar events, ongoing projects, and other connected information to summarize priorities and outstanding tasks. Users can delegate work through text or voice messages, including scheduling meetings, researching topics, preparing financial reports, and managing administrative workflows. The assistant can generate documents, spreadsheets, presentations, dashboards, and other deliverables using information retrieved from authorized applications. Claude Duet supports more than 6,000 connectors and plugins, including integrations with Gmail, Google Calendar, Slack, HubSpot, Salesforce, Shopify, QuickBooks, Notion, and Microsoft 365. Its persistent memory incorporates existing Claude conversations, saved context, skills, and connected tools to maintain continuity across tasks and interactions. The platform can continue working while users are away, monitor assigned activities, identify emerging issues, and provide notifications when tasks are completed or require intervention. Security and governance features include approval requirements for sensitive activities, isolated cloud execution, activity visibility, and the ability to review or redirect automated operations.

Meet your daily AI companion designed to uplift both your work and personal endeavors. With Copilot at your side, you can streamline your tasks, enhance your productivity, ignite your creativity, and nurture relationships with those who matter most—all while effortlessly adjusting to your unique preferences. This smart assistant offers cutting-edge solutions for maximizing efficiency and inventiveness, ensuring you remain connected to the important people and aspects of your life. Discover what you need with ease, receive helpful answers to your questions, and shop online with assurance, knowing that you're securing the best deals possible. Whether you're in search of quick information, inspiration for your creative projects, or support with your daily responsibilities, Copilot is here to effortlessly bring your visions to life. Creating captivating visuals and polishing your writing becomes a delightful journey, and regardless of your interests—be it exploring the web, acquiring new knowledge, tapping into your artistic talents, or producing meaningful content—Copilot paves the way for boundless opportunities for growth and discovery. Its adaptability makes it an essential resource for anyone eager to enhance their daily experience and embrace new possibilities. With Copilot, the path to achieving your goals and aspirations is clearer than ever. Copilot Vision, currently in preview for Microsoft Edge, enhances browsing by offering AI-driven assistance tailored to the content you view. This feature helps users by scanning pages, understanding context, and providing real-time suggestions or insights to improve the browsing experience. Whether it’s simplifying learning, aiding in decision-making, or helping with online shopping, Copilot Vision acts as a proactive assistant. It is an opt-in feature, prioritizing user privacy with all contextual data being erased after each use. With ongoing feedback, the feature is gradually expanding to more users and websites.

Muse Spark Open is a large-scale open-weight artificial intelligence model developed by Meta for multimodal understanding, software engineering, autonomous agents, and long-horizon reasoning. Released in October 2026, the model provides downloadable weights that allow developers to deploy and customize it outside Meta's hosted AI services. It uses a mixture-of-experts architecture containing 816 billion total parameters, with approximately 42 billion parameters activated during inference. Its one-million-token context window supports processing extensive documents, large software repositories, and lengthy sequences of instructions and interactions. The model is designed for complex coding workflows involving source code analysis, debugging, feature implementation, application development, and software testing. Its multimodal capabilities enable AI agents to interpret visual information and combine that understanding with reasoning and automated computer interactions. Meta demonstrated the model performing local software development tasks and controlling DaVinci Resolve to analyze video footage and prepare edited content. Muse Spark Open supports on-device deployment using two Apple M5 Ultra Mac Studio computers running the MLX framework, with additional compatibility across AMD, Intel, and NVIDIA hardware. Supported inference frameworks include SGLang, vLLM, TensorRT-LLM, Hugging Face Transformers, llama.cpp, and Unsloth, with optimized GPU kernels for improved processing performance. Developers can customize the model using PyTorch and TorchTitan to adapt its behavior to specialized tasks, organizational requirements, and application workflows. Muse Spark Open is distributed under the Muse Model License with limited commercial terms and is available through Hugging Face, Amazon SageMaker AI, Google Cloud Model Garden, Microsoft Foundry Models, and several hosted API providers.

Muse Ember is an efficient multimodal artificial intelligence model developed by Meta Superintelligence Labs for autonomous agent execution, coding assistance, complex reasoning, and large-scale business automation. The model is designed to handle the frequent, structured operations performed by AI agents, including tool calls, information retrieval, workflow routing, document extraction, and software development subtasks. It supports a context window of one million tokens and can generate up to 512,000 output tokens, allowing applications to process large repositories, extensive documents, and complex task histories. Muse Ember natively processes text, images, audio, video, and PDF content, enabling multimodal analysis without requiring separate models for each supported input type. Its visual understanding capabilities allow agents to interpret screenshots, charts, scanned documents, and interface elements while supporting computer-based automation workflows. Software engineering capabilities include reading source files, running tests, analyzing repositories, implementing targeted fixes, and completing programming tasks within autonomous coding environments. The model also supports enterprise automation workflows that involve retrieving information, evaluating records, executing tools in sequence, and updating data across connected business applications. Meta trained Muse Ember using Muse Wonder Full, creating a specialized model intended to combine strong reasoning capabilities with lower inference costs for frequently repeated tasks. Published evaluation results include 37.8% on AutomationBench-AA, 61.6% on Agents' Last Exam, 40.9% on Terminal-Bench 4.0, and 80.6% on PerceptionBench with tools. Muse Ember can be combined with larger models such as Muse Wonder and Muse Spark, allowing advanced models to handle planning and complex decisions while Ember performs high-volume execution tasks.

Hermes Agent by Nous Research is a powerful open-source autonomous AI agent designed to operate locally and evolve continuously based on user interactions and workflows. It differs from traditional AI assistants by maintaining persistent memory, allowing it to learn from past tasks and improve its capabilities over time. Running directly on a user’s server, Hermes provides full control over data and customization without reliance on centralized systems. The agent integrates seamlessly with multiple platforms such as Slack, Discord, Telegram, and WhatsApp through a unified messaging gateway. It supports advanced automation through natural language scheduling, enabling users to automate recurring tasks like reporting, backups, and briefings. Hermes can delegate tasks to isolated subagents, allowing parallel processing and efficient handling of complex workflows. It includes robust sandboxing options across environments like Docker, SSH, and local systems, ensuring secure execution of tasks. The platform also offers full web and browser control, including search, automation, and multimedia capabilities. Users can configure Hermes to work with various AI models or endpoints, providing flexibility and scalability. Its command-line interface enables deep customization and direct interaction with tools and processes. Hermes continuously updates and expands its capabilities through ongoing development and user feedback. Overall, Hermes Agent provides a highly adaptable, secure, and intelligent system for automation, development, and AI-driven workflows.

Muse Wonder is a frontier artificial intelligence model developed by Meta for advanced reasoning, autonomous agent workflows, personal assistance, and professional applications. Released in October 2026, the model belongs to the Muse Wonder family alongside Muse Wonder Full, a larger variant designed for computationally demanding tasks. The model incorporates Active Memory, a capability that preserves important contextual information across conversations and retrieves relevant details to support personalized assistance. Its Active Focus functionality enables sustained execution of complex objectives by exploring alternative solutions, adapting to new information, and working through obstacles. Muse Wonder can request clarification when instructions are incomplete and seek user approval before performing consequential actions. The model supports professional tasks involving legal analysis, financial information, health-related questions, research, and business process automation. Its agentic capabilities allow it to interact with connected applications, navigate browser-based workflows, and use external tools to complete multistep assignments. For software development, Muse Wonder can generate code, build applications, analyze existing projects, modify source files, and perform iterative testing and debugging. Meta trained the Muse Wonder series on diverse long-running tasks to improve performance on software engineering projects and unfamiliar problem-solving scenarios. The model has been evaluated using benchmarks such as MemoryBench, FocusBench, AutomationBench-AA, SWE-Marathon, and DeepSWE, with additional safety evaluations addressing privacy protection, adversarial instructions, and misuse prevention. Muse Wonder is available through the Meta Model API and Muse Code, while Muse Wonder Full is available to Muse Code subscribers, with broader integration into Meta's Muse assistant planned.

Meta Muse is a personal AI agent designed to take action across websites, apps, and everyday digital workflows on behalf of the user. Rather than functioning only as a conversational assistant, Muse can navigate the web, complete forms, book appointments, interact with customer service, and perform other multi-step tasks. It operates on a persistent dedicated virtual machine with its own browser, giving the agent an environment where it can continue working after a task has been assigned. Users can talk to Muse through the dedicated mobile app or through WhatsApp in a conversational format similar to ordinary messaging. The agent can connect to services such as email, calendars, Instagram, and other applications that are relevant to a user’s goals and routines. When given a broader objective, Muse can create an action plan, monitor progress, and return with suggestions or next steps as the situation develops. It can also build its own tools when a task requires functionality that is not already available through an existing integration. User control is built into the workflow through approval requirements for sensitive actions such as sending messages or making purchases. Muse maintains an audit trail that shows what the agent has completed and what it intends to do next. Security features include protected credential storage that the agent cannot directly read, planned 1Password integration, and one-time payment card numbers designed to reduce exposure of real card information during purchases. Meta Muse is intended for users who want a persistent AI agent that can coordinate personal tasks, work across digital services, and act autonomously within boundaries defined by the user.

Grok Bot is an AI teammate platform from SpaceXSI that helps users delegate operational work to bots that can act across apps, websites, tools, and routines. Instead of functioning only as a chat assistant, Grok Bot is designed to take real projects from start to finish and come back when user approval is needed. Bots can sign in to tools, use software like a person would, and work across desktop, mobile, and a persistent cloud computer. Users can create different bots for different responsibilities, such as sales outbound, talent scouting, paid media, expense management, product performance, bug reproduction, account health, and chief-of-staff tasks. A sales outbound bot, for example, can research accounts, score contacts using signals, draft emails and LinkedIn messages in the user’s voice, and hold messages for approval before sending. Grok Bot can learn workflows by watching a user complete a task once, then saving the process as a routine that can run again later. Bots can also work in parallel, collaborate in shared threads, and pass tasks between each other when a workflow requires more than one role. The platform supports scheduled routines so bots can continue working 24/7 across repeatable processes. Each user’s bots share one persistent cloud computer with shared files, browser sessions, and logins, allowing context to carry across work. Grok Bot is available across macOS, Windows, iOS, Linux, and other supported environments, with pricing options that include Cursor Ultra and Cursor Premium Teams. By combining agentic execution, tool access, persistent context, workflow learning, scheduled routines, multi-bot collaboration, and human approval, Grok Bot helps individuals and teams automate meaningful work across their stack.

Muse Code is Meta’s terminal-based AI coding agent built to take on complex software engineering tasks across large repositories. The agent is powered by Muse Spark 1.2 and is designed to plan code changes, write implementation code, validate results, and support end-to-end developer workflows. Muse Code can coordinate multiple persistent subagents for each task, helping solve difficult problems faster and with less manual intervention. Its architecture uses a simple agent loop enhanced by async background agents that remain active for the full session instead of being spawned only for individual steps. These background agents reduce repeated information gathering, carry out next actions, and communicate back to the main agent when useful. Muse Code’s runtime uses a local event log where model calls, tool runs, approvals, and edits are continuously appended. This event log serves as a single source of truth, making the runtime replay-exact and restart-safe if a crash or interruption occurs. The design allows Muse Code to handle long-running development work without losing progress or context. Muse Code includes bundled skills such as /plan for approval-gated task planning, /grill for stress-testing plans, and /goal for working toward successful completion of a defined objective. Example workflows include interpreting a video input, understanding the requested output, and producing a rich software experience such as a vacation home marketing and booking page. By combining terminal execution, autonomous planning, persistent background agents, replay-safe runtime design, bundled skills, and Muse Spark 1.2 model support, Muse Code helps developers complete ambitious coding tasks with greater reliability.

OpenAI Dots are always-on AI agents built to manage ongoing responsibilities and continue working on projects when the user is focused elsewhere. Powered by GPT-6 Astra, dots can proactively identify next steps, perform tasks, monitor developments, and return completed work or decisions requiring human judgment. Each dot can start with context from the user's ChatGPT memory and use Codex, connected tools, and its own cloud computer to perform work. Users decide which applications a dot can access, what responsibilities it should prioritize, and how tasks should be completed. A dot can be assigned an entire project or a smaller workflow and continue making progress between individual ChatGPT conversations. Example use cases include tracking product and revenue metrics while maintaining investor presentations, evaluating customer requirements for sales opportunities, managing API migrations, implementing software improvements based on customer feedback, and preparing content from transcripts. Dots can monitor new information as it arrives and update related work, allowing projects to remain current without requiring users to repeatedly restart the process. Users can inspect what their dot is doing, review details, provide feedback, redirect its work, or pause it whenever needed. Dots operate on independent cloud computers and support configurable permissions and Custom Rules that can allow actions, require approval, or block specific activities. Actions that could affect accounts or share information can go through Auto-review, which checks the proposed action against user instructions, Custom Rules, and safety requirements, while certain sensitive actions remain reserved for the user. Dots can be accessed through ChatGPT on web, mobile, and desktop, with availability across eligible Pro, Business Premium, and Enterprise plans and administrative enablement available for Enterprise environments.

Muse Spark 1.1 is an advanced multimodal reasoning model from Meta Superintelligence Labs built for agentic work, coding, computer use, tool calling, and multimodal understanding. It is a major upgrade from Muse Spark and is designed to push the performance-efficiency frontier for AI systems that need to plan, reason, act, and coordinate across complex workflows. The model can operate across external apps, native tools, MCP servers, custom skills, browsers, scripts, images, videos, PDFs, audio, and developer environments. Muse Spark 1.1 is especially strong in agentic orchestration, where it can gather context, make plans, delegate work to parallel subagents, and manage execution across multiple steps. As a subagent, it can follow a defined role, use available tools appropriately, and escalate back to a main agent when needed. Its 1 million token context window helps it remember past actions, retrieve information from earlier in a project, and compact long sessions while keeping important details available for later work. For computer-use tasks, Muse Spark 1.1 can navigate unfamiliar interfaces, adapt to changing requirements, and choose whether to click through an interface or write scripts when automation is faster. In software engineering, the model can diagnose complex bugs, implement new features, perform large code migrations, build web applications, inspect screenshots, trace issues to code, and validate fixes. Its multimodal capabilities allow it to inspect visual and audio information, generate detailed image and video captions, create visual-to-code artifacts, and combine perception with action in practical workflows. Developers can access Muse Spark 1.1 through Meta’s new Model API public preview, and everyday users can try it in Thinking mode in the Meta AI app.

Muse Spark 1.2 is a coding-focused AI model from Meta designed to support advanced software engineering tasks through Muse Code and the Meta Model API. The model builds on Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows. Muse Spark 1.2 powers Muse Code, a terminal coding agent that can plan repository changes, write code, validate outputs, and work across large codebases. Muse Code uses persistent async background agents that stay active throughout a session to reduce redundant information gathering and support difficult multi-step work. The runtime uses a local event log where model calls, tool runs, approvals, and edits are appended, making sessions replay-exact and restart-safe. Muse Spark 1.2 was co-trained with Muse Code so the model can take advantage of its toolset, harness workflows, goals, compaction, and subagent architecture. Meta significantly scaled training compute on coding tasks and expanded training environment diversity to improve the model’s engineering capabilities. The model was also trained on long-horizon coding tasks, including whole-repository generation, large end-to-end projects, auto-research, and extended iterative work. Its training approach uses planning, goal conditioning, context compaction, rejection-sampled harness trajectories, and self-improvement data generated with Muse Spark 1.1. Meta also tested Muse Spark 1.2 on long-running GPU kernel optimization workflows where the model wrote, compiled, profiled, and improved Triton kernels over many tool calls. By combining coding-focused training, agentic runtime integration, persistent subagents, long-horizon reasoning, replay-safe execution, and API availability, Muse Spark 1.2 helps developers and AI agents complete complex software engineering work with less intervention.

OpenClaw is a powerful open-source AI assistant that functions independently on your computer, server, or VPS, going beyond mere text generation to perform real-world tasks in response to your natural language commands through widely-used messaging platforms like WhatsApp, Telegram, Discord, and Slack. By tapping into various external large language models and services, it prioritizes local processing and data security, allowing the assistant to proficiently handle your inbox, send emails, manage your calendar, check you in for flights, interact with files, execute scripts, and optimize daily workflows without depending on predetermined triggers or cloud-based systems. Designed to have a persistent memory, OpenClaw can retain context across multiple sessions and operate continuously, thus taking the initiative in task and reminder management. Furthermore, it enables seamless integrations with messaging applications and supports community-created "skills," providing users with the flexibility to expand its capabilities and oversee various agents or tools within distinct workspaces. This makes OpenClaw not only a versatile tool for personal productivity but also a customizable platform that adapts to individual needs and preferences. Ultimately, its ability to learn and evolve with user interactions enhances the overall experience, ensuring that it remains relevant and highly effective in managing tasks.

Muse Video is Meta’s previewed AI video generation model from Meta Superintelligence Labs, created to bring high-quality video generation into Meta AI and creator workflows. It was introduced alongside Muse Image as one of Meta’s first media generation models from the new lab, with both models sharing the same pretraining foundation. Muse Video is designed to create short videos with strong prompt adherence, visual fidelity, temporal consistency, and native audio support. The model can generate scenes that include realistic motion, camera movement, environmental sound, voice, music, foley, and cinematic structure. Example use cases include animal clips, product ads, first-person nature footage, vertical UGC-style commercials, branded video concepts, and short continuous scenes with a clear beginning, action, and payoff. Muse Video is built for prompts that require both visual and audio direction, such as synchronized speech, diegetic sound, music beds, product sound effects, and natural scene ambience. Meta says the model performs competitively on human-preference video generation benchmarks and is continuing to improve in areas where video models often struggle. Those areas include better audio-video synchronization, more physically accurate fast motion, and stronger consistency across complex moving subjects. The model is expected to come soon to creators and Meta AI, where it will expand Meta’s generative tools beyond still images into dynamic video content. Meta also plans to extend its Content Seal watermarking system to video, helping people identify AI-generated media. By combining video generation, native audio, realistic scene construction, and future integration across Meta products, Muse Video is positioned as a major creative tool for social content, advertising, storytelling, and brand media.

Hark Pro is a personal AI platform designed to function as an intelligent assistant capable of reasoning, remembering context, and performing actions for users. Rather than limiting the experience to answering questions, Hark Pro is built to carry out practical tasks across applications and websites. Users work with the platform through a continuing conversation, while persistent memory can retain authorized information from previous inputs, outputs, actions, and connected accounts. Hark Pro can connect with services including email, calendars, documents, and messaging tools and use those services to complete authorized tasks. The platform can also generate materials such as documents and web pages while supporting proactive and scheduled actions for work that needs to occur later, repeatedly, or when specified conditions are satisfied. Its computer-use capabilities extend the assistant to the open web by allowing it to navigate graphical interfaces with browser actions such as clicking, scrolling, and typing. Hark Pro can operate within a dedicated virtual computing environment containing a browser, file system, and terminal for completing more complex internet tasks. Connected accounts can provide relevant information such as preferences, addresses, and account history when Hark Pro performs authorized actions for the user. Applications include shopping and checkout, restaurant and food ordering, travel reservations, online research, and recruiting activities such as discovering and contacting candidates. Hark Pro supports multimodal interactions including chat, voice, file uploads, and agentic sessions, providing multiple ways for users to communicate instructions and supply information. By bringing together conversational AI, persistent memory, connected services, multimodal interaction, computer use, and autonomous task execution, Hark Pro is designed to serve as a personalized AI assistant for managing digital work and everyday activities.

Manus is a versatile general AI agent that seamlessly bridges the gap between concepts and actions, enabling it to perform a wide array of tasks in various professional and personal contexts. From managing data analysis and organizing travel plans to creating educational materials and offering stock market evaluations, Manus assists users in reaching their objectives while allowing them to focus on other significant responsibilities. Its functions include conducting detailed research, designing captivating presentations, and analyzing market trends, all designed to boost productivity and optimize efficiency. Additionally, Manus generates accurate, actionable insights, positioning itself as an essential tool for both professionals and everyday individuals who seek to simplify their workflows and gain deeper insights into their tasks. By fusing cutting-edge technology with an intuitive user interface, Manus serves as an invaluable ally in navigating the intricacies of contemporary life. Ultimately, its comprehensive capabilities make it a reliable partner for anyone looking to enhance their daily operations and decision-making processes. Manus Desktop with the “My Computer” capability transforms how an AI agent interacts with a user’s personal computing environment by enabling direct access to local files, tools, and applications. It operates through command line execution, allowing the AI to perform a wide range of actions, including reading, editing, organizing, and managing files efficiently. This makes it highly effective for automating repetitive and time-consuming tasks such as file organization, bulk renaming, and data processing. Beyond simple automation, it supports full-scale development workflows by utilizing local programming tools like Python, Node.js, Swift, and other environments to build, debug, and deploy applications.

ChatGPT Work functions as an innovative assistant within the ChatGPT ecosystem, empowering users to manage extensive projects by overseeing tasks across different applications and documents while dedicating significant time to ensure successful project completion. This tool efficiently aggregates information from diverse sources to generate thorough outputs, including spreadsheets, presentations, written content, and web apps, simplifying complex tasks into achievable steps and executing them independently while keeping the user updated on progress, addressing questions, adjusting priorities, and recommending essential actions. Thanks to its integrated Codex technology and the backing of GPT-5.6, ChatGPT Work goes beyond conventional question-response interactions to enable genuine task execution across web, mobile, and desktop environments. Users can ask it to analyze monthly budget discrepancies, create marketing campaign frameworks from raw data, prepare for sales meetings, or maintain continuity throughout a project, spanning from initial consumer insights to the development of marketing materials and adaptations for specific markets. This adaptability not only allows users to optimize their workflows substantially but also boosts efficiency and guarantees that every detail is meticulously attended to in achieving their objectives. Moreover, the seamless integration of ChatGPT Work into daily operations illustrates its potential to transform how users approach their project management and execution strategies.

Hermes Business functions as a collaborative workspace tailored for the deployment of the Hermes AI agent developed by Nous Research. This platform enables organizations to manage a centralized AI agent that assists with research, programming, web tasks, and various intricate projects. Administrators within teams are granted the authority to regulate member access, distribute a shared budget, and implement individual spending caps. The service is designed for teams that want to make the agent accessible across the organization while maintaining necessary administrative control. Available through the Nous Portal, it’s essential to clarify that this description focuses on the hosted business solution instead of a separate server product. Additionally, the features for structured access and budget management significantly boost organizational productivity and resource distribution, ensuring teams can operate more effectively. With these tools, organizations can streamline their processes and maximize the potential of the Hermes AI agent.

The Meta Model API serves as a groundbreaking developer interface that leverages Muse Spark 1.1, Meta's cutting-edge multimodal reasoning model specifically designed for agentic applications such as programming, tool use, and extensive computer interactions. Currently in its public preview phase, this API allows developers to easily integrate Muse Spark 1.1 through an OpenAI-compatible package, ensuring a smooth transition for current clients while preserving the existing code structure and facilitating straightforward adjustments to the muse-spark-1.1 model. This model is particularly adept at performing personal agentic tasks, enabling effective planning and coordination across a range of external applications and services, in addition to its ability to adapt to new native tools, MCP servers, and customized skills. When functioning as a primary agent, it can gather contextual information, formulate plans, and supervise actions across multiple subordinate agents; however, as a subagent, it focuses on its specified responsibilities, understands the tools at its disposal, and knows when to escalate concerns. Furthermore, the model boasts the capacity to handle a context window of 1 million tokens, which empowers it to remember previous actions, retrieve information from much earlier tasks, and condense context for enhanced efficiency. As a result of these features, the Meta Model API signifies a major leap forward in the creation of intelligent and responsive software applications, paving the way for future innovations in technology. This advancement not only benefits developers but also enhances the user experience by enabling more sophisticated interactions with digital tools.

Claude Cowork is Anthropic’s autonomous desktop AI assistant designed to transform how professionals manage information-intensive work. Operating directly within a user’s local environment, the platform can access files, folders, and applications to execute complex workflows including document creation, research analysis, information extraction, and file management. Claude Cowork is built to handle high-effort, repetitive tasks independently by understanding desired outcomes and completing the required steps without constant user guidance. With a focus on productivity, human oversight, and responsible AI deployment, the platform helps organizations streamline operations, improve information accessibility, and generate high-quality deliverables faster while allowing users to remain in control of critical decisions.

Muse Spark is an advanced multimodal AI model developed by Meta Superintelligence Labs, representing a major step toward personal superintelligence. It is built from the ground up to integrate text, images, and tool-based interactions, enabling more dynamic and intelligent responses. The model features visual chain-of-thought reasoning, allowing it to process and explain visual information in a structured way. It also supports multi-agent orchestration, where multiple AI agents collaborate to solve complex problems efficiently. Muse Spark introduces Contemplating mode, which enhances reasoning by enabling parallel agent workflows for higher accuracy and performance. The model demonstrates strong capabilities in areas such as STEM reasoning, health analysis, and real-world problem-solving. It can generate interactive experiences, such as visual annotations, educational tools, and personalized insights. Muse Spark is trained using a combination of advanced pretraining, reinforcement learning, and optimized test-time reasoning strategies. Its architecture focuses on scaling efficiency, achieving strong performance with reduced computational requirements. Safety is a key priority, with built-in safeguards, alignment mechanisms, and robust evaluation processes. The model is available through Meta AI platforms, with API access in limited preview. Overall, Muse Spark represents a significant evolution in AI, moving closer to highly personalized, intelligent assistants that understand and interact with the real world.

Muse Wonder Full is a large-scale artificial intelligence model developed by Meta for advanced agentic reasoning, professional knowledge work, and complex software engineering tasks. Introduced in October 2026, it represents the larger variant of the Muse Wonder family and builds on Meta's research into scaling pretrained models and reinforcement learning. The model is designed to manage complex objectives involving multiple steps, changing requirements, external information, and sustained problem-solving. Its Active Memory capability maintains important contextual information across conversations and retrieves relevant details when they become useful for subsequent tasks. Active Focus enables the model to pursue long-running assignments, explore alternative strategies, recover from obstacles, and adapt to new information. The system can request clarification when instructions are incomplete and seek user confirmation before performing important actions. Muse Wonder Full supports professional applications involving legal documents, financial analysis, health-related information, and business process automation. Its coding capabilities include generating software, analyzing existing repositories, tracking implementation requirements, modifying source code, and performing iterative testing and debugging. Meta trained the model on diverse long-running software engineering tasks to support development projects requiring multiple rounds of implementation and revision. Evaluations include MemoryBench for contextual memory, FocusBench for sustained task execution, SWE-Marathon and DeepSWE for software engineering, and additional assessments covering professional agents and unfamiliar problem-solving tasks. Muse Wonder Full is available to Muse Code subscribers, with Meta also reporting safety evaluations addressing personal information handling, adversarial instructions, unauthorized code execution, and misuse prevention.

TrustClaw functions as a 24/7 AI assistant, equipped with over 1,000 integrations through OAuth and operating within a highly secure, sandboxed setting, fundamentally reimagined with a security-first approach inspired by OpenClaw principles. This advanced assistant is designed to handle various tasks autonomously while users are at rest, enabling smooth communication with the same agent across multiple messaging platforms like Telegram, with plans to extend support to WhatsApp, Discord, and Slack soon. Users can count on TrustClaw to streamline their workflows by efficiently retrieving and organizing emails, crafting replies, documenting customer feedback in Notion, summarizing Slack messages, extracting completed tickets from Linear, and generating release notes. In addition, it has the capability to scrape reviews, analyze sentiment, keep tabs on Gmail for customer queries, and seamlessly integrate with a wide range of applications, including Gmail, GitHub, Notion, Figma, Linear, Jira, Google Drive, Google Calendar, Todoist, Asana, Trello, Stripe, HubSpot, and Airtable, among others. A paramount aspect of the platform is its dedication to enhancing security, removing the reliance on insecure password or API-key-based configurations in favor of OAuth-only connections and encrypted credential management, thereby ensuring a safer user experience. In essence, TrustClaw not only aims to revolutionize user interaction with AI but also seeks to establish a new standard for efficiency and security in managing digital tasks, setting the stage for a more productive future.

Muse Image is Meta’s image generation model from Meta Superintelligence Labs, built to help people create visuals that feel personal, contextual, and easy to share. Available through Meta AI, the model can generate new images from scratch, transform existing photos, blend multiple visual references, erase unwanted elements, and create images with clean, readable text. Users can ask for anything from a historical travel mockup or custom postcard to a product image, illustrated guide, room redesign, social sticker, fantasy scene, poster, infographic, or stylized portrait. Muse Image is designed to understand conversational prompts, so users do not need to write complex technical instructions to get detailed results. The model works with Muse Spark to reason through a request before producing the final image, helping it plan the layout, use real-time web context, and combine multiple inputs more accurately. Meta AI includes more than 30 suggested presets to help users quickly try popular ideas, such as restoring old family photos, testing hairstyles, creating claymation versions of themselves, or becoming a 16-bit video game character. Muse Image also supports image personalization through @ mentions, allowing users to bring public Instagram profiles into creative prompts when permitted by privacy settings. For edits, users can tap the markup icon, sketch directly on the image, circle areas to change, add notes, and keep refining without restarting the entire creation. The model also powers creative experiences on Instagram and WhatsApp, including AI effects for Instagram Stories and image generation in direct chats with Meta AI. Meta plans to expand Muse Image to Facebook, Messenger, more Instagram and WhatsApp surfaces, and Meta Advantage+ creative for advertisers and agencies.

Fregio is an innovative AI-powered platform designed for WordPress, featuring Muse, an AI assistant that supports users in the creation, management, verification, and protection of genuine WordPress sites. Instead of just constructing a website, Fregio oversees the entire website lifecycle, which includes updating content, altering designs, verifying site functionality, configuring domains and SSL certificates, as well as monitoring security. Specifically designed for small businesses, agencies, freelancers, startups, and creative professionals, Fregio seeks to reduce the manual effort involved in both building and maintaining WordPress sites. Users have full control over their WordPress sites, inclusive of content and administration, while utilizing AI to improve both the development journey and the ongoing management of their websites. By simplifying these processes, Fregio allows users to dedicate more time to their primary business pursuits rather than getting bogged down in the technical aspects of website maintenance. This emphasis on efficiency not only enhances productivity but also empowers users to make the most of their digital presence.

Muse Glimmer is a cutting-edge model boasting 30 billion parameters, crafted by Meta Superintelligence Labs, specifically optimized for seamless local agent functionality. Its streamlined architecture enables operation on standard Mac or PC systems with a single consumer GPU, making it suitable for a range of applications, including local agent management, programming tasks, function invocation, and evaluations within LLM-as-a-judge scenarios, all without needing cloud services or an internet connection. This groundbreaking model features sophisticated abilities like long-horizon execution, precise tool invocation, multimodal understanding, expanded memory for contextual awareness, and proficient instruction adherence. It excels in performing comprehensive tasks as an agent, adeptly navigates complex multi-step reasoning across extensive workflows, and can recover effectively from unexpected tool interactions. Additionally, it interprets interleaved text and images through a specialized perception encoder tailored for analyzing screenshots, graphs, and various document types. Beyond its primary functions, Muse Glimmer is designed to work harmoniously with OpenClaw and other orchestration frameworks, allowing for customizable reasoning capabilities and has been trained on a rich dataset that spans over 100 languages. The adaptability of this model not only enhances its effectiveness across different fields but also positions it as a significant asset in the evolving landscape of AI applications. Its innovative features and user-friendly deployment make it a versatile choice for professionals seeking to leverage AI for complex problem-solving.

Muse Voice Transcribe marks Meta's first foray into the realm of real-time audio processing, delivering immediate automatic speech recognition (ASR), speaker identification, and endpointing features. This autoregressive multimodal model, a part of the Muse Spark series, evaluates audio snippets lasting 80 milliseconds and swiftly determines whether to continue listening or transcribe the spoken content into text. Its adaptive delay mechanism fine-tunes the audio context for each word based on the speech's complexity, thereby improving both transcription accuracy and response speed. The model is trained in over 70 languages, with 25 being thoroughly validated upon its launch, and it effectively manages arbitrary code-switching, enabling smooth transitions within and between sentences. Additionally, features for language, keyword, and contextual biasing significantly boost the model's ability to recognize particular names, locations, contacts, and specialized terminology. With its streaming diarization capability, the model adeptly identifies changes in speakers and can distinguish between over 20 different voices. The endpointing feature is also proficient at recognizing when speech begins and ends, contributing to a seamless interaction experience. As a result, Muse Voice Transcribe emerges as an innovative tool in speech recognition technology, cleverly combining advanced functionalities with ease of use while continuing to evolve based on user feedback and advancements in the field.

Microsoft has unveiled Muse, a groundbreaking generative AI model that is set to revolutionize how gameplay ideas are conceived. Collaborating with Ninja Theory, this World and Human Action Model (WHAM) utilizes data from the game Bleeding Edge, enabling it to understand 3D game environments along with the complexities of physics and player dynamics. This proficiency empowers Muse to produce diverse and coherent gameplay sequences, thereby enhancing the creative workflow for developers. Furthermore, the AI possesses the ability to craft game visuals while predicting controller inputs, thus facilitating a more efficient prototyping and artistic exploration phase in game development. By analyzing over 1 billion images and actions, Muse not only demonstrates its promise for game creation but also for the preservation of gaming history, as it has the ability to resurrect classic titles for modern platforms. Even though it is currently in its early stages and produces outputs at a resolution of 300×180 pixels, Muse represents a significant advancement in utilizing AI to aid in game development, aiming to boost human creativity rather than replace it. As Muse continues to develop, it may pave the way for groundbreaking innovations in gaming and the resurgence of cherished classic games, potentially reshaping the entire gaming landscape.