Alternatives to Muse

Muse Spark Open is an open-weight foundation model developed by Meta to support multimodal reasoning, autonomous agents, and complex software development tasks. The model features 816 billion total parameters with approximately 42 billion active parameters and a context window supporting up to one million tokens. Its architecture is designed to process multimodal information while maintaining context across lengthy workflows, extensive codebases, and multistep assignments. Muse Spark Open provides capabilities for software engineering, code generation, debugging, application development, and automated testing. Its agentic functionality supports external tool interactions, task planning, computer-based workflows, and execution of complex objectives over extended sessions. The model can run locally using two Apple M5 Ultra Mac Studio systems with the MLX framework, enabling organizations to process information without relying on hosted inference services. Developers can deploy the model through SGLang, vLLM, TensorRT-LLM, Hugging Face Transformers, llama.cpp, and other supported inference engines. Customization is supported through PyTorch and TorchTitan, allowing organizations to adapt the model to specialized applications and workflows. Muse Spark Open is distributed under the Muse Model License and is available through Hugging Face, major cloud model repositories, and hosted API providers including Together AI, Fireworks AI, and OpenRouter.

Perplexity Computer is a super agent platform that autonomously executes complex projects based on simple user instructions. Instead of requiring step-by-step prompting, users describe their desired end product, and the system decomposes the task into coordinated workflows handled by multiple AI models. It supports website creation, in-depth research reports, structured datasets, and multimedia production within one unified interface. The system intelligently routes tasks to the most appropriate models for research, visual generation, video production, or rapid search. Built for long-running execution, it can manage multi-stage assignments independently for extended periods. By removing the need to manually select or switch between AI tools, it simplifies sophisticated workflows into a seamless experience. The platform emphasizes outcome delivery rather than model management. Its orchestration layer ensures efficiency, adaptability, and task-specific optimization. Perplexity Computer enables users to move from concept to completed project with minimal friction. It represents a shift toward fully autonomous AI systems designed to handle end-to-end digital production.

Codex is an advanced AI coding assistant from OpenAI that helps developers streamline the entire software development process from start to finish. It functions as a powerful pair programmer capable of understanding repositories, writing code, and generating production-ready pull requests. The platform supports complex workflows, including debugging, refactoring, testing, and code reviews, all within a unified environment. One of its standout features is computer use, which allows Codex to operate your computer directly by seeing the screen, clicking, and typing within applications. This capability enables it to interact with tools and software that lack direct integrations or APIs. Codex also includes an in-app browser, allowing developers to iterate on web applications and provide precise instructions directly on live pages. It integrates with a wide range of tools and plugins, enhancing its ability to gather context and take action across workflows. The platform supports multi-agent collaboration, enabling parallel work across projects to accelerate development timelines. Codex also offers automation features that allow it to schedule and complete recurring tasks without manual input. With memory capabilities, it can remember preferences and past actions to improve future performance. Overall, Codex delivers a comprehensive AI-powered solution that combines coding, automation, and real-world computer interaction to boost developer efficiency.

Muse Wonder is an advanced AI foundation model developed by Meta to support personal AI agents, professional knowledge work, and software engineering tasks. The model is part of the Muse Wonder series, which includes Muse Wonder and the larger Muse Wonder Full variant. 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 multistep objectives, evaluate alternative approaches, respond to obstacles, and continue working toward completion. Muse Wonder supports applications involving legal document analysis, financial information, health-related questions, and business workflow automation. Its coding capabilities include generating applications, modifying existing codebases, tracking project requirements, and iterating through testing and debugging cycles. The model can operate as part of agentic systems that interact with browsers, external applications, and connected tools to complete user-directed activities. Meta has evaluated Muse Wonder on benchmarks covering personal assistance, professional agent tasks, long-term memory, sustained execution, and software development. Muse Wonder is accessible through the Meta Model API and Muse Code, with plans to incorporate its capabilities into the Muse assistant and additional AI-powered experiences.

Grok Bot is an AI teammate platform that allows users to assign work to bots across their tools, apps, websites, and business workflows. The platform is designed for AI agents that can sign in to tools, operate them like a user would, and complete projects from start to finish. Users can message bots like teammates on desktop or iOS, give them tasks, and receive completed work or approval requests when needed. Grok Bot supports multiple bots working at once, making it possible to run one bot for outbound sales, another for expenses, another for inbox management, and another for systems or project operations. Bots can learn by watching a user complete a workflow, save that process as a routine, and repeat it later on a schedule. They keep context over time, learn from each other, and can collaborate inside shared threads by passing work between bots. Example workflows include researching accounts, scoring contacts, drafting email and LinkedIn messages, managing receipts, clearing inboxes, preparing follow-ups, booking venues, and creating recap documents. The platform includes a persistent cloud computer that bots share, allowing them to keep files, browser sessions, logins, and context available across work. By combining agentic task execution, tool access, workflow learning, scheduled routines, multi-bot collaboration, and approval checkpoints, Grok Bot helps users turn AI into an active teammate.

OpenAI Dots are persistent AI agents powered by GPT-6 Astra that can independently make progress on projects while remaining under the user's direction. A dot functions as an extension of its user by learning how they work, monitoring what requires attention, and using its own cloud computer to carry out tasks between conversations. It can begin with context from ChatGPT memory and use Codex and connected tools to work with relevant applications, documents, data, and workflows. Users can give a dot responsibility for a large project or a smaller recurring workflow and allow it to proactively determine appropriate next steps. Dots can analyze new data, refresh reports and presentations, investigate unexpected results, prepare code and tests, monitor feedback, and draft supporting materials for review. They can also maintain continuity across related tasks, such as updating an investor presentation when new financial data arrives or tracking an API migration until remaining dependencies are resolved. Users can communicate with their dots through ChatGPT on web, mobile, and desktop to provide feedback, change direction, or review work in progress. Permissions and Custom Rules determine which applications a dot can access, which actions it can perform independently, and which activities require explicit approval. Potentially consequential actions are subject to additional review against the user's instructions, configured rules, and applicable safety requirements.

Instinct serves as a personal assistant that grasps your ongoing projects and what matters most to you, seamlessly linking to the applications and devices that encapsulate the context of your daily routine. It operates across various platforms such as email, messaging, your screen, audio, and location, eliminating the need for you to transition everything to a new interface. The design of the interaction is intentionally straightforward, so there's no need to learn any additional interfaces. Instinct is adept at utilizing both phones and computers just as users naturally do, with accessibility via text or voice calls. Its fundamental model is specifically developed to comprehend and address the intricate personal details of daily life, enabling it to go beyond merely responding to isolated queries to actively managing ongoing tasks and unresolved matters. This assistant can proactively re-engage in conversations you may have left hanging, alert you when certain issues require your attention, organize your airport transportation, or even schedule a handyman for your apartment, ensuring that you can focus on what truly matters without the stress of managing every detail yourself. Through its thoughtful integration into your life, Instinct becomes an invaluable partner in navigating the complexities of everyday responsibilities.

Hermes Agent by Nous Research is an open-source autonomous AI system designed to function as a persistent, self-improving digital assistant. Unlike traditional AI tools, it runs locally on your server, allowing it to retain memory and learn from ongoing interactions over time. The agent integrates with multiple communication platforms, including Slack, Discord, Telegram, and WhatsApp, enabling seamless cross-platform usage. Hermes supports automation through natural language scheduling, allowing users to set up recurring tasks such as reports, backups, and updates. It can execute complex workflows by delegating tasks to subagents that operate in parallel environments. The platform includes advanced capabilities like web browsing, search, code execution, and multimedia processing. It also offers secure sandboxing options across multiple environments, including Docker and local systems. Hermes can be configured to use different AI models or APIs, giving users flexibility in deployment. Its command-line interface provides a powerful and customizable interaction experience. Overall, Hermes Agent delivers a scalable, adaptable, and intelligent solution for automation and task management.

Muse Spark 1.1 is Meta’s upgraded multimodal reasoning model designed to support advanced agentic workflows, coding tasks, computer use, and complex tool orchestration. Developed by Meta Superintelligence Labs, it builds on Muse Spark with major gains in planning, tool use, long-context reasoning, multimodal perception, and real-world task execution. The model can work across external apps and services, native tools, MCP servers, custom skills, browsers, scripts, images, video, PDFs, and audio inputs. Muse Spark 1.1 can act as a main agent by gathering context, creating a plan, and delegating work to parallel subagents, or operate as a subagent that follows instructions and escalates when needed. Its 1 million token context window allows it to retain earlier actions, retrieve information from long workflows, and compact context while preserving critical details. The model is also trained for computer-use tasks, deciding when to automate with scripts and when to interact directly with an interface. In coding workflows, Muse Spark 1.1 can diagnose bugs, implement features, migrate large codebases, generate web applications, take screenshots, identify UI issues, and validate fixes. Its multimodal strengths include visual-to-code generation, detailed image and video captioning, grounded perception, and workflows where seeing, reasoning, and acting happen together. Available through the Meta Model API public preview and in Thinking mode inside Meta AI, Muse Spark 1.1 gives developers and users a more capable foundation for building agents, automations, coding assistants, and multimodal productivity tools.

Muse Code is a beta terminal coding agent from Meta designed to help developers complete complex software engineering work across large codebases. Powered by Muse Spark 1.2, the agent can plan repository changes, write code, run validation steps, and coordinate persistent subagents for difficult development tasks. Muse Code uses a simple main agent loop supported by async background agents that remain active throughout each session. These background agents can gather information, carry out next steps, and decide when to report back to the main agent, reducing latency and unnecessary user steering. The runtime is built around a local event log where every model call, tool run, approval, and edit is appended. This event log makes Muse Code replay-exact and restart-safe, allowing it to resume from the point of failure after a crash. Muse Code also ships with default skills, including /plan, /grill, and /goal, to support structured planning, plan validation, and objective completion. It can be installed on macOS or Linux and is integrated with Meta’s AI developer ecosystem. By combining terminal-based coding, persistent subagents, replay-safe execution, bundled skills, and Muse Spark 1.2, Muse Code helps developers automate larger and longer software engineering workflows.

Muse Video is Meta’s upcoming AI video generation model developed by Meta Superintelligence Labs as part of the company’s new media generation lineup. Previewed with Muse Image, the model is built on the same pretraining base and is designed to produce visually detailed videos with native audio support. Muse Video is focused on generating clips that follow prompts closely, maintain strong visual fidelity, and preserve temporal consistency across motion and scene changes. It can create realistic short videos with clear beginnings, actions, and payoffs, such as animals moving through a scene, handheld first-person footage, product commercials, and UGC-style social ads. The model supports audio-rich outputs that may include environmental sound, foley, music, voiceover, and synchronized spoken dialogue. Meta highlights Muse Video’s ability to handle cinematic prompts, vertical ad formats, realistic camera movement, product demonstrations, and emotionally engaging creative concepts. The company is still investing in improvements for difficult areas such as audio-video sync and physically accurate fast motion. Muse Video is expected to become available to creators and in Meta AI, expanding Meta’s generative AI tools from image creation into video. As part of Meta’s broader creative ecosystem, Muse Video is built to help users, creators, and businesses turn prompts into dynamic, shareable video content.

Muse Spark 1.2 is Meta’s newest coding-focused model, released alongside Muse Code as part of Meta’s AI developer platform. The model improves on Muse Spark 1.1 with stronger code generation, complex debugging, codebase understanding, and full developer workflow performance. Muse Spark 1.2 powers Muse Code, a terminal coding agent that can plan changes, write code, validate results, and coordinate persistent background subagents. The model was co-trained with Muse Code so it performs well inside the agentic coding runtime and tool environment. Its training included scaled coding compute, broader training environment diversity, rejection-sampled harness trajectories, recipe optimizations, and Muse Code toolset integration. Muse Spark 1.2 is designed for long-horizon coding tasks such as whole-repository generation, large end-to-end projects, auto-research, and extended optimization work. It uses planning to sequence work, goal conditioning to stay aligned with the user’s objective, and context compaction to preserve useful knowledge over long sessions. The model also benefits from a self-improvement loop where Muse Spark 1.1 generated challenging coding environments and instruction-following templates for training. By combining coding specialization, agentic workflow support, long-horizon training, subagent compatibility, and Meta Model API availability, Muse Spark 1.2 helps developers build, debug, and optimize software more effectively.

Muse for Small Business extends Meta's Muse personal AI agent with skills and connectors designed around the day-to-day needs of small business owners. Rather than only responding to individual questions, Muse can take on tasks and projects, work in the background, and translate long-term goals into ongoing action plans. Users can give Muse a goal once and have the agent continue working toward it while returning with progress updates, ideas, and decisions that require attention. Business use cases include preparing client pitches, creating product pages, planning marketing content, developing advertisements, drafting customer communications, managing inventory, and assisting with cash flow. Muse learns from conversations and reflects on the user's priorities so its recommendations and actions can become more closely aligned with the business over time. It can connect with applications including Asana, Box, Canva, Dropbox, Figma, Granola, HighLevel, QuickBooks, Klaviyo, Lovable, Notion, Shopify, Slack, Stripe, and Zoom. Connections to Facebook, Instagram, and Meta ads provide additional business context and allow Muse to help analyze and improve advertising and content. Actions such as sending emails and making purchases can require user approval, while a complete audit trail shows what the agent has done and what it intends to do next. Muse also incorporates security measures such as secure credential storage integrations and one-time card numbers for supported shopping transactions, while Meta states that Muse conversations are not shared with its advertising systems.

OpenClaw is a versatile open-source AI assistant that operates autonomously on your computer, server, or VPS, surpassing the basic function of text generation by executing real-world tasks based on your natural language commands via popular messaging platforms such as WhatsApp, Telegram, Discord, and Slack. By connecting to various external large language models and services, it emphasizes local processing and data control, enabling the assistant to efficiently manage your inbox, send emails, organize your calendar, check you in for flights, interact with files, execute scripts, and streamline daily workflows without relying on predefined triggers or cloud-based solutions. It is designed to maintain persistent memory, which allows it to remember context across different sessions and run continuously, thereby proactively managing tasks and reminders. Additionally, OpenClaw facilitates integrations with messaging applications and supports community-developed "skills," empowering users to enhance its functionality and manage various agents or tools within separate workspaces, making it an adaptable solution for personal productivity.

Limova serves as a cloud-based AI platform that assists businesses by automating repetitive tasks across various areas including marketing, sales, customer service, administration, and operations. Users can assign responsibilities to specialized agents that handle tasks such as creating social media content, writing search-optimized articles, conducting prospect research, answering customer queries, and managing telephone reception. The platform integrates with a range of business tools such as email, calendars, messaging apps, CRM systems, cloud storage, and social media networks, enabling agents to execute actions within connected workflows seamlessly. A central assistant is available to oversee the work of these specialized agents, while users have the ability to set instructions, offer business context, manage permissions, and monitor activity. This service caters to a wide array of clients, including entrepreneurs, freelancers, startups, small to medium-sized enterprises, and larger corporations aiming to streamline their tasks without requiring any coding expertise. Ultimately, Limova empowers organizations to focus on growth and innovation by significantly reducing the burden of manual processes.

Manus is a multifaceted general AI agent that effectively connects ideas with actions, allowing it to carry out various tasks in both work and personal environments. Whether it's handling data analysis, organizing travel itineraries, developing educational resources, or providing stock market insights, Manus empowers users to accomplish their goals while attending to other important matters. Its capabilities extend to conducting intricate research, crafting engaging presentations, and interpreting market dynamics, all aimed at enhancing productivity and streamlining efficiency. Furthermore, Manus produces precise, actionable insights, establishing itself as a vital resource for both professionals and everyday users aiming to simplify their workflows and achieve a greater understanding of their tasks. By integrating advanced technology with user-friendly functionality, Manus becomes an indispensable companion in navigating the complexities of modern life. Manus Desktop with the “My Computer” capability allows an AI agent to work directly on a user’s local device, extending its functionality beyond cloud-based environments. It uses command line access to read, modify, and organize files, as well as launch and control local applications and tools. This enables users to automate time-consuming tasks such as sorting files, batch renaming documents, and managing workflows with minimal effort. The platform also supports advanced development capabilities, allowing the AI to build, debug, and deploy applications using local programming environments like Python, Node.js, and Swift. By bridging cloud intelligence with local system resources, it enhances productivity and unlocks new automation possibilities.

Tab is an AI personal assistant that enables users to complete everyday tasks and manage digital workflows through standard text messaging. Rather than simply providing instructions or recommendations, the assistant can take actions such as booking travel, changing reservations, making purchases, and contacting businesses. Users can send natural-language requests along with photos, screenshots, PDFs, and videos to provide context for their tasks. Tab can extract information from documents, convert PDFs into spreadsheets, create files, edit images and videos, and generate multimedia content. The assistant operates through its own computer and browser, allowing it to navigate websites, complete forms, and interact with connected user accounts. Its phone calling capabilities enable it to contact hotels, restaurants, medical offices, and other businesses to ask questions, make arrangements, or modify appointments. Tab maintains conversation history and task context so users can return to ongoing work without repeating previous instructions. For longer assignments, the assistant provides brief progress updates and continues processing tasks while users attend to other activities. When a task requires payment, Tab displays the transaction details and requests explicit approval before completing the purchase, then provides receipts and follow-up information through the same messaging conversation.

Wix's Symphony is an innovative AI platform designed for independent entrepreneurs and small business ventures seeking assistance with managing ongoing tasks. At its core, the platform features Maestro, an intelligent agent that acquires knowledge about the business and assigns responsibilities to specialized agents adept in areas like outreach, marketing, scheduling, research, finance, and content development. Users can seamlessly integrate tools such as calendars, emails, productivity applications, Slack, and Salesforce, while monitoring agent performance within a collaborative workspace that displays task updates, business overviews, and key performance indicators. Teams have the flexibility to design personalized agents, approve or modify crucial actions, and oversee operations through an intuitive conversational interface. Symphony is accessible both as a web application and a mobile app, offering users a choice between free and premium subscription options, thus catering to a diverse range of business needs. This multifaceted approach empowers users to optimize their workflow while ensuring they stay on top of their operational goals.

Aidan serves as an innovative platform designed to develop AI-driven employees capable of managing live customer calls on a large scale, employing real-time browser engagement and advanced computer vision technology. It integrates a constantly evolving context graph that encompasses a company’s products and optimal communication strategies with the capability to manipulate software during interactions. By utilizing real-time computing, Aidan can actively showcase workflows rather than merely explaining them, and its vision system enables a pixel-level guided experience for customers as they navigate the product. Organizations can enhance Aidan’s functionality by sharing recordings of their top sales conversations, insights from internal specialists, and promotional content, allowing them to modify its appearance, tone, and behavior to align with their brand identity. Furthermore, Aidan has the ability to initiate product demonstrations and qualification processes without requiring additional integrations, gradually increasing its expertise as it encounters more customer interactions, thus enriching its context graph continuously. This ongoing evolution fosters a more personalized and effective customer experience over time.

Spinnable offers AI-driven virtual employees that autonomously manage repetitive business tasks within the existing software that teams already utilize, functioning continuously around the clock. Each AI worker is designed for a particular role or process and can operate based on a predetermined schedule or be activated by specific events, all without the need for any technical configuration. The range of available AI workers includes capabilities in areas such as product management, executive assistance, financial analysis, research, real estate operations, sales, customer service, and general operations. These intelligent assistants can perform a variety of tasks, including researching potential clients, following up on leads, drafting product requirement documents and tickets, managing appointments and email correspondence, analyzing financial data, tracking market trends, publishing content, collecting invoices, handling routine customer inquiries, and generating regular reports. Additionally, these workers can integrate with over 50 different tools like Gmail, HubSpot, Notion, Google Sheets, Google Calendar, Stripe, Outlook, Salesforce, Intercom, GitHub, Jira, Zendesk, and Asana, allowing them to read, modify, and take action across the entire technological landscape as if they were a part of the team. This seamless integration ensures that teams can focus on higher-level tasks while the AI handles the more mundane aspects of their workflow.

Backdrop is a platform driven by artificial intelligence that enables organizations to assemble the AI workforce necessary for their operations by generating AI assistants tailored for various tasks. Each assistant can be equipped with the essential tools, context, and guidance to conduct research, develop projects, coordinate efforts, follow up, and manage workflows comprehensively. The platform excels in analyzing and synthesizing data related to markets, competitors, customers, and internal metrics, transforming raw information into actionable summaries, detailed reports, and insightful recommendations. AI assistants are capable of developing marketing initiatives, creating content, managing outreach, providing client updates, and executing follow-ups, in addition to constructing dashboards, automating repetitive tasks, tracking problems, testing software releases, and establishing integrations. With support for over 1,000 integrations and advanced access controls, Backdrop effectively consolidates business operations. Its collaborative memory feature retains the lessons learned and decisions made by teams, agents, and projects, significantly minimizing the need for repetitive context. This innovative approach fosters efficiency and collaboration, making it easier for teams to achieve their objectives.

AI Workers are independent agents crafted specifically for your organization; these advanced AI entities function like genuine colleagues rather than mere chatbots awaiting instructions. Each comes equipped with its own professional identity, including an email, phone number, and presence on platforms like Slack and Teams, demonstrating initiative and the capacity to operate around the clock without needing prompts. Rather than dictating every detail of their tasks, you simply define the objectives, and they autonomously develop the necessary workflows, accommodating a variety of tasks such as generating daily reports, conducting weekly follow-ups, managing CRM updates, handling client interactions, performing research, overseeing content creation, executing finance responsibilities, coordinating HR activities, supporting design projects, and assisting with development operations. This system includes a diverse range of specialized AI Workers tailored for functions in marketing, development, design, HR, finance, and more, with each worker crafted for a specific role and practical applications. Furthermore, AI Workers can integrate seamlessly with over 3,000 tools, such as Slack, Microsoft Teams, Gmail, Notion, HubSpot, Salesforce, and various other business applications, ensuring they fit effortlessly into your existing workflows. Their versatility and adaptability make them an invaluable asset for enhancing productivity and streamlining processes in any business environment.

ChatGPT Work serves as a proactive assistant within ChatGPT, enabling users to tackle larger projects by actively managing tasks across various applications and documents, dedicating hours to ensure a project reaches completion. This tool can gather data from multiple sources to produce comprehensive deliverables such as spreadsheets, presentations, written documents, and web applications, effectively breaking down intricate assignments into manageable steps and executing them autonomously while keeping the user informed of progress, answering queries, shifting priorities, and endorsing key actions. With its integrated Codex technology and support from GPT-5.6, ChatGPT Work transcends traditional question-answering capabilities to facilitate actual task completion on web, mobile, and desktop platforms. Users might request it to evaluate a monthly budget variance, develop marketing campaign outlines from raw materials, prepare for sales discussions, or maintain context throughout a project, from initial customer insights to the creation of marketing assets and adaptations for the market. This versatility allows users to streamline their workflows significantly, enhancing productivity and ensuring that no detail is overlooked in the execution of their goals.

Claude Cowork is an AI-powered productivity platform that autonomously handles knowledge work tasks across local files, applications, and business documents. Built for non-technical users, the platform allows professionals to delegate complex workflows such as document preparation, research synthesis, data extraction, and file organization without needing technical expertise or manual prompt engineering. Claude Cowork navigates multiple information sources, processes large volumes of content, and delivers structured outputs while maintaining human oversight for important decisions. Its desktop-based approach enables seamless interaction with the tools and files employees already use, helping organizations improve efficiency, reduce administrative workloads, and accelerate decision-making.

Construct Computer serves as a cloud-centric AI agent workspace tailored for individual entrepreneurs and small groups. Users can delegate tasks using either a browser-based desktop or a chat-optimized web interface. The agents within the platform have the capability to search the internet, navigate interactive websites, execute code in a secure sandbox environment, manage files, create documents, and utilize various connected applications. This workspace is equipped with features such as persistent files and memory, an email inbox for agents, a calendar, reusable workflows, records of activities, and shared resources for teams. Users have the ability to review or modify memory and can monitor or halt the agents' progress. Construct Computer integrates seamlessly with platforms like Slack, Telegram, and Discord, along with a selection of services from its Composio integration catalog; additionally, workspaces can employ custom MCP servers and private applications. Agents are able to assign limited subtasks and execute scheduled jobs in the cloud environment. Subscription plans impose restrictions on agents, including limits on task steps, scheduled activities, concurrent jobs, command execution time, and storage space. Furthermore, a mobile web interface is accessible through smartphone browsers, although the vendor clarifies that it is not an App Store application. Overall, Construct Computer aims to streamline workflow management for its users by offering a diverse array of functionalities and integrations.

CellCog serves as an innovative platform for integrating AI employees into various roles, allowing them to collaborate, onboard, and manage their responsibilities autonomously. Each AI employee possesses a distinct identity, complete with an email inbox, task board, dashboards, and persistent memory, all while operating under permissions that owners can customize. At the core of CellCog is the advanced super-agent, which ranked #1 on the DeepResearch Bench in July 2026 and is capable of generating research, code, dashboards, PDFs, videos, images, and spreadsheets efficiently. In addition to its employee capabilities, CellCog offers interactive chat modes, access to a desktop for collaborative work, a Chrome extension for browser tasks, over 1,000 tool connectors, and a Python SDK for further integration. New users can kick off their experience with 200 complimentary credits upon signup, with no credit card required; typically, a full-time AI employee costs between $500 and $1,000 per month, with a usage fee of around $25 per shift. Designed specifically for small to medium-sized businesses and solo entrepreneurs, this platform provides an effective solution for replacing costly specialist work that often exceeds $5,000 per month. By streamlining operations and reducing overhead costs, CellCog empowers businesses to harness the full potential of AI in their daily functions.

Hark Pro is a personal AI platform designed to help users delegate digital tasks and manage everyday work through an ongoing AI conversation. The system can remember permitted information from conversations, outputs, actions, and connected accounts, allowing its assistance to become more personalized over time. Hark Pro can work with connected services such as email, calendars, documents, and messaging tools and take authorized actions on a user's behalf. It can also create documents, web pages, and other materials directly from user instructions. Its computer-use technology is designed for autonomous, multi-step work across websites and other browser-based interfaces. Hark Pro can use a virtual computer containing a browser, file system, and terminal, enabling it to interact with websites through their interfaces rather than relying exclusively on APIs. This allows the platform to perform tasks such as ordering products and food, booking restaurants, arranging travel, researching information across multiple websites, and assisting with recruiting workflows. Hark Pro also supports proactive and scheduled actions that can run later, recur on a schedule, or execute when specified conditions are met. By combining persistent memory, multimodal AI, connected applications, content creation, and autonomous computer use, Hark Pro provides a centralized AI assistant for completing personal and professional tasks.

Feather serves as a desktop AI assistant tailored for professional knowledge tasks, operating seamlessly within folders on a Mac as well as in linked SharePoint and Google Drive directories. Users can communicate their tasks using everyday language, allowing Feather to read and modify files directly, thus generating or updating various work products like Word documents, Excel spreadsheets, and PowerPoint presentations. Every request is processed in an individual workstream, enabling users to monitor the modifications made by Feather. This versatile tool facilitates workflows across various domains, including litigation, investigations, intellectual property, tax, consulting, and business operations. Currently, it is designed for Macs equipped with Apple silicon, with plans for a Windows version to be released in the near future. As technology evolves, Feather aims to enhance collaboration and efficiency in professional settings.

Hermes Business serves as a collaborative workspace specifically designed for utilizing the Hermes AI agent from Nous Research. This platform allows organizations to have centralized management of an AI agent capable of aiding in research, coding, web-based tasks, and other complex projects. Team administrators are empowered to control access for members, allocate a communal budget, and impose individual spending restrictions. The service caters to teams aiming to provide agent access organization-wide while ensuring that administrative oversight is maintained. Offered via the Nous Portal, it is important to note that this description pertains to the hosted business solution rather than a standalone server product. Furthermore, the structured access and budget management features enhance organizational efficiency and resource allocation.

Gemini Spark is an AI-powered personal automation agent developed by Google to help users manage digital workflows, automate repetitive tasks, and streamline productivity across connected applications and services. Built on Gemini 3.5 and powered by the Antigravity harness, Spark extends the capabilities of Gemini beyond question answering by acting as a proactive AI partner that can execute tasks and coordinate workflows under user supervision. The platform integrates with Google Workspace tools such as Gmail, Docs, Slides, and additional connected applications to automate information processing, task management, summarization, and workflow execution. Gemini Spark operates as a cloud-based AI agent that continues working in the background even when users close their laptops or mobile devices, enabling uninterrupted automation and ongoing task execution. Users can create recurring triggers, monitor inbox activity, generate summaries, extract deadlines, draft documents, and automate communication workflows through natural language instructions. The platform also supports skill training, allowing users to teach Spark how to handle specific recurring tasks and workflows tailored to personal or professional needs. Google is expanding Spark’s ecosystem through MCP integrations with services such as Canva, OpenTable, and Instacart, with additional partner integrations planned to support broader automation capabilities. Future features will include custom sub-agents, browser operation support, and the ability to interact with Spark through email and text messaging. Gemini Spark is designed with user oversight and security controls that require approval before high-stakes actions such as sending emails or making purchases are completed.

Muse Image is Meta’s first image generation model from Meta Superintelligence Labs, designed to make Meta AI a more capable creative assistant for visual content creation. The model allows users to generate images from simple prompts, edit existing photos, blend multiple images, remove unwanted background elements, and create polished visuals that can be shared across chats, stories, feeds, and other Meta surfaces. It supports a wide range of creative styles, including photorealistic portraits, Renaissance paintings, 16-bit characters, claymation scenes, stickers, movie posters, product shots, room makeovers, infographics, and stylized illustrations. Muse Image is built to reason through prompts before creating an image, using Muse Spark to plan composition, incorporate real-time web context, and combine different visual references into a coherent output. Meta AI also includes presets to help users start quickly, such as restoring an old family photo, trying a new hairstyle, reimagining a person as a game character, or generating a themed visual effect. Users can personalize images by @-mentioning public Instagram profiles in the Meta AI app and can control whether their own content is available for this kind of AI creation. The editing experience lets users circle, sketch, or mark up changes directly on an image while Meta AI keeps track of the conversation context. Muse Image is available in Meta AI and also powers new creative tools in Instagram Stories and WhatsApp, with Facebook, Messenger, and advertiser availability planned. By combining generation, editing, personalization, and sharing, Muse Image gives users a flexible way to turn everyday ideas into high-quality visual content.

The Meta Model API is an innovative developer interface designed for utilizing Muse Spark 1.1, Meta's advanced multimodal reasoning model tailored for agentic tasks such as coding, tool utilization, and comprehensive computer interactions. Currently available in public preview, this API enables developers to seamlessly integrate Muse Spark 1.1 via an OpenAI-compatible package, simplifying the transition for existing clients while maintaining the same code framework and allowing for easy configuration to the muse-spark-1.1 model. This model excels in personal agentic functions, facilitating planning and coordination across various external applications and services, while also adapting to new native tools, MCP servers, and bespoke skills. Functioning as a primary agent, it can collect contextual information, devise plans, and oversee execution across multiple subagents; conversely, as a subagent, it adheres to its designated role, comprehends available tools, and recognizes when to escalate issues. Additionally, the model is capable of managing a context window of 1 million tokens, allowing it to remember past actions, retrieve information from significantly earlier tasks, and effectively condense context for optimal performance. With these capabilities, the Meta Model API represents a significant advancement in the development of intelligent, responsive applications.

Muse Wonder Full is a frontier AI model developed by Meta to support advanced reasoning, personal assistance, professional workflows, and autonomous software development. It is the larger model variant in the Muse Wonder series, which also includes the standard Muse Wonder model. The system combines Active Memory and Active Focus to maintain relevant context and sustain progress on complex assignments. Active Memory enables the model to preserve important information across conversations and retrieve details relevant to current objectives. Active Focus supports multistep execution by allowing the model to investigate alternative solutions, respond to obstacles, and adjust its approach as tasks evolve. Muse Wonder Full can assist with legal document analysis, financial reasoning, health-related information, and other knowledge-intensive activities. Its software engineering capabilities support code generation, application development, debugging, testing, and modifications across existing codebases. Meta has evaluated the model using benchmarks such as MemoryBench, FocusBench, SWE-Marathon, DeepSWE, and professional agent assessments. Muse Wonder Full is accessible through Muse Code subscriptions and is intended for tasks that require extended reasoning, contextual continuity, and coordinated AI agent execution.

Muse Spark is Meta’s first model in the Muse family, designed as a natively multimodal AI system focused on advanced reasoning and real-world applications. It combines text, visual understanding, and tool usage to provide more interactive and context-aware responses. The model introduces capabilities like visual chain-of-thought reasoning and multi-agent orchestration for complex problem-solving. Its Contemplating mode allows multiple AI agents to work in parallel, improving accuracy on challenging tasks. Muse Spark performs strongly across domains such as STEM reasoning, health insights, and multimodal perception. It can analyze images, generate interactive outputs, and assist with tasks like troubleshooting or educational content. The model is trained using improved pretraining, reinforcement learning, and efficient test-time reasoning techniques. It is designed to scale efficiently while delivering high performance with optimized compute usage. Safety measures include strong refusal behavior and alignment safeguards across high-risk domains. Overall, Muse Spark is a foundational step toward building personalized, highly capable AI systems.

VidMuse serves as an innovative AI-driven music video creator that swiftly converts audio tracks into stunning cinematic visuals. Users can easily upload their music through various platforms, including links from Suno, Udio, Spotify, or YouTube, or by using MP3 or WAV files. The platform meticulously analyzes various elements of the track, such as rhythm, lyrics, and emotional dynamics, crafting a comprehensive musical blueprint rather than simply overlaying visuals. Acting as an intelligent director, VidMuse interprets the audio to develop a detailed plan for the video even before production commences. It employs advanced audio intelligence, a creative brief, storyboarding, and precision controls, culminating in a one-click production process. With each project, VidMuse produces a Director's Script that outlines visual styles, scenes, pacing, and storyboards, allowing creators to evaluate and adjust their vision prior to the final render. Additionally, users can select from various templates like Story MV, Abstract MV, and Viral Short, while having the freedom to personalize elements such as the narrative, visual aesthetics, camera techniques, character designs, and scene dynamics through an interactive chat interface, enhancing the creative process even further. Ultimately, VidMuse empowers artists to envision and realize their music video concepts with unprecedented efficiency and creativity.

Muse Glimmer is an open-weights model featuring 30 billion parameters, developed by Meta Superintelligence Labs, and is fine-tuned for continuous local agent operations. Its compact design allows it to function on a standard Mac or PC equipped with a single consumer GPU, making it ideal for various tasks such as local agent management, function calling, programming, and LLM-as-a-judge evaluations without reliance on cloud services or internet connectivity. This innovative model integrates advanced capabilities such as long-horizon execution, accurate tool invocation, multimodal comprehension, extended memory for context, and effective instruction following. It is proficient in accomplishing end-to-end tasks as an agent, maintains the ability to engage in multi-step reasoning over lengthy processes, can recover gracefully from failed or unanticipated tool engagements, and interprets interleaved text and images using a specialized perception encoder designed for analyzing screenshots, graphs, and document files. Furthermore, Muse Glimmer is compatible with OpenClaw and other orchestration frameworks, allowing for adjustable reasoning efforts, and has been developed with a diverse dataset encompassing over 100 languages. The model's versatility ensures that it can adapt to various applications, thus enhancing its utility in different domains.

MuseClass streamlines the process of creating, sharing, and assessing assignments all within a single platform. Students can easily capture videos using the MuseClass mobile app on their smartphones, and once they submit their best version, you can review their performances through the grading interface in your teacher portal. Additionally, students have the option to record audio directly via the app; after submitting their recordings, you'll be able to listen to them conveniently on the grading screen. For in-person evaluations, you can quickly enter scores into MuseClass, ensuring that all grades and feedback for your students are consolidated in one location. The integrated gradebook simplifies monitoring student development over time. You can also upload worksheets that students can complete independently, and after finishing their assignments, they can simply snap a photo with the MuseClass app to submit their work for your evaluation. This comprehensive approach not only enhances learning but also saves valuable time for educators.

Microsoft has introduced Muse, an innovative generative AI model poised to transform the way gameplay concepts are developed. In partnership with Ninja Theory, this World and Human Action Model (WHAM) draws training data from the game Bleeding Edge, granting it a profound grasp of 3D game landscapes, including the intricacies of physics and player interactions. This capability allows Muse to generate varied and coherent gameplay sequences, which can enhance the creative process for developers. Additionally, the AI is capable of creating game visuals and anticipating controller actions, streamlining prototyping and artistic exploration in game design. By leveraging an analysis of over 1 billion images and actions, Muse showcases its potential not only for game creation but also for game preservation, as it can recreate classic titles for contemporary gaming platforms. Despite being in its initial phases, with output currently limited to a resolution of 300×180 pixels, Muse signifies a pivotal step forward in harnessing AI to support game development, with the goal of amplifying human creativity rather than supplanting it. As Muse evolves, it may open up new avenues for both game innovation and the revival of beloved gaming classics.

MuSES achieves unparalleled accuracy in electro-optic and infrared renderings through a systematic process that starts with the identification of heat sources like engines, exhaust systems, bearings, and electronic components, followed by a comprehensive in-band diffuse radiosity solution. After establishing your sensor at a specified range, you can render multi-bounce radiance values that have been spectrally summed, utilizing DeltaT-RSS contrast metrics for detailed analysis. If you have a sensor response curve available, simply import it to uncover insights you may have overlooked. With MuSES, you can explore reality in unprecedented detail. The software’s capability extends to comprehensively address physics from heat sources to environmental influences, enabling you to effectively manage thermal signature contrasts and assess control kits essential for low observable design in any geographical context. You can rigorously evaluate heat shields, cooling methods, and camouflage surface treatments for in-band radiance while accounting for atmospheric attenuation along the sensor’s line-of-sight. By prioritizing engineering tasks with MuSES early in your project development cycle, you empower your team to make informed decisions that enhance overall design effectiveness. This foresight can significantly streamline the development process and improve project outcomes.

We have developed MuseNet, an advanced deep neural network capable of producing 4-minute musical pieces featuring 10 distinct instruments, while seamlessly merging genres ranging from country to the classical compositions of Mozart and even the iconic sounds of the Beatles. Rather than being programmed with musical knowledge, MuseNet identifies and learns patterns of harmony, rhythm, and style through the process of predicting the subsequent token in a vast collection of MIDI files. This innovative model employs the same unsupervised technology as GPT-2, a robust transformer model designed to anticipate the next token in a sequence, whether it pertains to audio or text. Thanks to MuseNet's understanding of diverse musical styles, we are able to create unique blends of musical generations. We eagerly anticipate the creative ways in which both musicians and those without formal training will leverage MuseNet to craft original compositions! Users can select a composer or style and optionally begin with a well-known piece, allowing them to delve into the rich array of musical styles that the model can produce. This opens up exciting possibilities for artistic exploration and experimentation.

MuseMail is an innovative email creation tool powered by artificial intelligence, aimed at assisting users in crafting stunning and professional emails swiftly. By simply entering a prompt, users can generate complete HTML emails in mere seconds, eliminating the hassle of starting from the beginning when composing messages. The platform offers over 95 distinct styles tailored to various industries, ensuring that your emails align perfectly with your target audience or specific campaign objectives, whether they involve marketing promotions, newsletters, product launches, or other forms of business communication. After generating an email, users have the option to utilize a visual editor to adjust design features and customize content prior to sending, which allows for precise control over layout, imagery, and branding while still harnessing the efficiency of AI. MuseMail functions as a comprehensive email studio, streamlining the creative workflow so that professionals can minimize tedious manual edits and concentrate on strategic planning and audience engagement. This seamless process not only enhances productivity but also promotes creativity, making it a valuable tool for any email marketing effort.

Muse Voice Transcribe represents Meta’s inaugural venture into real-time audio perception, providing instantaneous automatic speech recognition (ASR), speaker diarization, and endpointing capabilities. This autoregressive multimodal model, part of the Muse Spark series, analyzes audio segments of 80 milliseconds and makes real-time decisions on whether to keep listening or to convert the spoken words into text. The adaptive delay mechanism allows it to adjust the audio context utilized for each word according to the complexity of the speech, thus optimizing the balance between transcription precision and response time. With training encompassing over 70 languages, 25 of which were rigorously validated at the time of its release, the model also seamlessly accommodates arbitrary code-switching, allowing transitions within and across sentences. Furthermore, language, keyword, and contextual biasing features enhance the recognition capabilities for specific names, locations, contacts, or specialized terms. The streaming diarization functionality enables the model to recognize shifts in speakers and can differentiate between more than 20 individual voices. Additionally, the endpointing feature is adept at identifying the commencement of speech and knowing when a user has completed their statement, ensuring a fluid interaction experience. Overall, Muse Voice Transcribe stands out as a cutting-edge tool in the realm of speech recognition technology, merging advanced features with user-friendly application.

Tidy is an innovative platform that leverages artificial intelligence to serve as a personal agent, assisting users in automating various tasks and developing customized tools without the need for coding skills. Users can swiftly create their own personal agent and engage with it through user-friendly messaging platforms, facilitating effective communication and execution of tasks within diverse workflows. The platform is adaptable enough to interface with nearly any website or application, allowing the agent to undertake activities that users typically handle manually, such as monitoring updates or managing daily online responsibilities. Additionally, Tidy provides a range of integrated and community-driven tools to streamline the setup process, including features like reminders for upcoming tasks and a persistent memory for storing notes and files. By linking with services such as Google Calendar, Tidy can discern user availability and automatically assist in scheduling events. Ultimately, Tidy aims to establish itself as a versatile, no-code automation solution that observes and responds to user habits, ensuring consistent execution of repetitive digital tasks while enhancing overall productivity. This approach not only saves time but also empowers users to focus on more strategic activities.

Muses serves as an advanced writing assistant powered by artificial intelligence, designed to streamline the content creation process by offering professional-level support without the need for installations or extensive learning. It enables users to effortlessly transition between various top-tier AI models, catering to diverse creative preferences and requirements. The innovative "Tab to Flow" feature remains unobtrusive until activated, delivering intelligent completions that help sustain writing flow, while "Spark to Story" transforms fleeting notes or bursts of inspiration into comprehensive narratives. Users can easily upload reference materials, allowing the AI to generate content that is well-informed and backed by their research, with all produced text undergoing automatic verification for factual accuracy to enhance trustworthiness. Additionally, Muses aggregates pertinent information from across the internet, gathering resources that enrich articles, blog entries, promotional content, and extensive writing projects. Designed to foster creativity with ease, it merges cutting-edge AI technology, real-time support, and rigorous validation, ensuring a seamless writing experience that empowers users to elevate their work effortlessly. The platform's user-friendly nature encourages writers of all levels to explore their creativity without the barriers typically associated with writing tools.

Muse is a cutting-edge AI tool created by Sudowrite, a startup based in Los Angeles, and is tailored specifically for writers of fiction. In contrast to more generalized AI systems, Muse is dedicated solely to the art of narrative prose, showcasing sophisticated storytelling abilities and the capacity to produce extensive, engaging chapters that are both creative and coherent. Drawing from the expertise of over 20,000 writers, Muse aspires to deliver original and compelling narratives that steer clear of clichés, fully embracing the complexities of human experiences, including multifaceted characters, morally ambiguous situations, and rich imagery, all without imposing any restrictions or obligatory happy endings. Seamlessly integrated into the Sudowrite platform, it functions as a collaborative ally for authors, bolstering their creative journey with tools for crafting captivating openings, authentic dialogue, and significant text generation, while ensuring the distinct voice of the writer remains intact. This innovative approach empowers writers to explore new storytelling horizons, ultimately enriching the landscape of modern fiction.