The Future of Productivity is Voice: Introducing 11.ai by ElevenLabs
John: In the ever-evolving landscape of artificial intelligence, we’re constantly seeing innovations that promise to reshape how we interact with technology. This week, we’ve seen a particularly interesting development from ElevenLabs, a company already renowned for its cutting-edge voice synthesis. They’ve unveiled 11.ai, a voice-first AI assistant designed not just to answer questions, but to take action and manage tasks. This isn’t just another chatbot, Lila; it’s a significant step towards truly conversational and actionable AI, aiming to streamline workflows and enhance productivity through natural voice commands. It’s built on the premise that voice can be a more intuitive and efficient interface for many of our daily digital chores, from scheduling meetings to conducting research and even managing complex project tasks across various platforms. The potential here, especially for busy professionals and teams looking for seamless integration, is quite substantial. It’s currently in an early phase, described as a prototype or an alpha, but the vision is clear: to make interacting with our digital tools as simple as having a conversation with a capable assistant.
Lila: Wow, John, that sounds like a game-changer! So, when you say “voice-first,” does that mean it *only* works with voice, or is it more about voice being the primary, most natural way to use it? And what makes this “actionable” aspect different from, say, asking my current phone assistant to set a reminder?
Basic Information: What is 11.ai?
John: That’s an excellent clarifying question, Lila. “Voice-first” in the context of 11.ai means that the system is fundamentally designed and optimized for voice interaction. While there might be supplementary ways to interact, perhaps typing for certain inputs or clarifications – indeed, some early user feedback mentions a desire for a typing option – the core experience revolves around speaking your commands and receiving spoken or integrated responses. Think of it as moving beyond the often clunky voice commands we’re used to, towards a more fluid, conversational paradigm. The “actionable” part is where it truly aims to differentiate itself. While current assistants can set reminders or play music, 11.ai is designed for deeper integration into your digital workflows. It’s about delegating multi-step tasks that involve other applications. For instance, instead of just reminding you to email someone, 11.ai might be able to help you draft that email or log a follow-up task in your project management tool, all initiated by voice. It’s about performing tasks that have tangible outcomes within your work ecosystem.
Lila: So, it’s like having a real assistant who can actually *do* things in my apps, not just tell me things? That sounds incredibly useful. Who exactly is behind 11.ai, and what’s their main goal with this?
John: Precisely. The company behind 11.ai is ElevenLabs. They’ve made a significant name for themselves in the AI space, particularly for their highly realistic and emotive AI-generated voices. You might have encountered their technology in various applications, from content creation to accessibility tools. Their expertise in voice AI is a natural foundation for building a sophisticated voice assistant. The main goal, as articulated in their announcements, appears to be leveraging this voice technology to create an assistant that transcends simple Q&A. They want 11.ai to be a genuine productivity partner, one that can understand complex instructions, interact with other software, and automate tasks that would otherwise require manual navigation through multiple interfaces. It’s about reducing friction in our digital lives and making technology adapt to us, rather than the other way around. The emphasis is on “actionable productivity” – using voice to directly manage tasks, conduct research, and communicate more efficiently.
Lila: That makes a lot of sense, especially coming from a company that masters voice. So, if I understand correctly, 11.ai is essentially a personal AI assistant that you talk to, and it helps you get work done by interacting with your other digital tools? Is it aimed at individuals, or more for teams and businesses?
John: You’ve got the core concept right, Lila. It is indeed a personal AI assistant, designed to be interacted with primarily through voice, and its key function is to perform tasks and manage workflows by connecting with various digital tools you already use. As for the target audience, the initial descriptions and capabilities suggest it’s highly beneficial for individuals seeking to enhance personal productivity – think busy professionals, freelancers, or even students juggling multiple projects. However, the ability to integrate with collaborative tools like Slack or project management platforms like Notion and Linear also points towards significant potential for team-based applications. Imagine a team member verbally updating a task status in Linear or asking 11.ai to summarize recent Slack discussions on a project. While it’s presented as a “personal” assistant now, the underlying technology could certainly scale or be adapted for broader organizational use in the future, fostering more efficient team collaboration through a centralized, voice-driven interface.
Supply Details: Availability and Access
Lila: This sounds amazing! If it’s so new, how can people actually get their hands on it? Is it widely available, or is it one of those things you have to join a long waitlist for?
John: Given its recent unveiling, 11.ai is currently in its very early stages. According to the announcements, it’s available as a “proof of concept” in an alpha testing phase. This means it’s not yet a fully polished, commercially released product. Alpha testing is typically an internal or limited external phase where developers gather initial feedback on functionality and identify bugs. Some sources mention that you can try it for free, which is common for alpha programs to attract testers and gather diverse usage data. Interested users would likely need to sign up or apply for access, possibly through the ElevenLabs website or a dedicated portal for 11.ai. It’s positioned as an experiment to showcase the potential of conversational AI that can take action, so early adopters will be crucial in shaping its development. So, no, not widely available off-the-shelf just yet, but the doors seem to be opening for those keen to explore its capabilities at this nascent stage.
Lila: “Proof of concept” and “alpha testing” – got it. So, it’s more for the tech enthusiasts and early adopters right now who don’t mind a few rough edges. Is there any talk about pricing yet, or is it completely free during this alpha phase?
John: Typically, alpha and even beta phases for products like this are offered free of charge to encourage participation and feedback. The search results, like the one from ZDNet, explicitly state, “you can try it for free.” This aligns with the standard practice. The primary goal for ElevenLabs at this point isn’t monetization of 11.ai itself, but rather to test the technology, understand user behavior, demonstrate the capabilities, and refine the product based on real-world usage. Long-term pricing models, if and when 11.ai moves towards a commercial release, haven’t been detailed. They could adopt various strategies – a subscription model, tiered features, or perhaps integrating it as a premium feature within a broader ElevenLabs ecosystem. For now, the focus is on development and user experience, with accessibility being key to gathering that vital early feedback. So, for the foreseeable future, those accepted into the alpha program should be able to explore 11.ai without a price tag.
Lila: That’s great news for anyone curious to try it out! So, if someone is interested, they should probably head over to the ElevenLabs website and look for sign-up information for the 11.ai alpha program?
John: That would be the most logical first step, Lila. Companies usually announce such programs on their official websites or dedicated product pages. The LinkedIn posts from ElevenLabs and their team members also point towards this early access. Keeping an eye on ElevenLabs’ official channels, including their social media and any product pages specifically for 11.ai, would be the best way to find information on how to participate. It’s also worth noting that alpha programs can sometimes be rolled out in waves, so even if access isn’t immediate, registering interest early is always a good idea. And for those who do get access, their feedback will be invaluable to ElevenLabs as they work towards making 11.ai a more robust and widely available tool. This early interaction between developers and users is critical for shaping the final product into something truly useful and intuitive.
Technical Mechanism: How Does 11.ai Work?
John: Now, let’s delve into the “how,” which is always fascinating. At the heart of 11.ai’s ability to perform actions is a concept some sources refer to as MCP, which likely stands for something like “Model-Controller-Periphery” or a similar architectural pattern. Essentially, the “Model” would be the advanced AI, including large language models (LLMs) for understanding your natural language requests and ElevenLabs’ own sophisticated speech recognition and synthesis technologies to process your voice and respond. The “Controller” acts as the brain, interpreting your intent and figuring out what actions need to be taken across different applications. And the “Periphery” refers to the connections or integrations with external tools and services – your Slack, Google Calendar, Perplexity for research, Notion for notes, Linear for project tracking, and so on. So, when you speak a command, 11.ai processes the voice, understands the task, and then the controller uses these peripheral connections to execute the task in the relevant app.
Lila: MCP – Model, Controller, Periphery. That actually makes it sound quite organized! So, it’s not just one giant AI brain, but a system where different parts specialize in understanding, deciding, and then doing, using these connections to other apps. You mentioned Perplexity – is that the search engine? How would 11.ai use that?
John: Precisely, Lila. Perplexity AI is indeed an AI-powered search and conversational answer engine. The integration with Perplexity means you could ask 11.ai complex questions or request research on a topic, and it would leverage Perplexity’s capabilities to find and synthesize information for you, likely presenting it back vocally or in a summarized text format if applicable. For example, you could say, “11.ai, what are the latest advancements in quantum computing, and summarize the key challenges?” 11.ai would then, through its MCP architecture and integration, query Perplexity and deliver the answer. This goes beyond simple keyword search; it’s about getting comprehended, summarized information directly through your voice assistant. This integration is a key part of its “actionable” nature, turning information retrieval into a seamless part of your workflow without you needing to open a browser and type queries manually. It makes 11.ai a research assistant as well as a task manager.
Lila: That’s incredibly powerful, especially for those of us who do a lot of research. What about the voice itself? Given it’s from ElevenLabs, I imagine the voice quality is top-notch, but can you customize it? And how does it handle understanding different accents or noisy environments?
John: ElevenLabs is a leader in realistic voice synthesis, so yes, the expectation is that the voice output of 11.ai will be exceptionally natural and human-like. Some reports mention access to over 5,000 different voices, which suggests a high degree of personalization will be possible, allowing users to choose a voice that they find pleasant or that suits their preferences. This is a significant step up from the often robotic or limited voice choices in many current assistants. As for understanding different accents and noisy environments, these are common challenges for any voice recognition system. ElevenLabs has been working on robust speech-to-text (STT) technology, and the more data these systems are trained on, the better they become at handling variations in speech and ambient noise. In an alpha phase, this is one of the aspects that will be rigorously tested. The quality of the microphone used will also play a role, of course. The aim is for the interaction to feel as natural and effortless as talking to a human, which means robust understanding is paramount. Their experience with diverse voice data for synthesis likely gives them an edge in developing tolerant recognition models too.
Team & Community: The People Behind 11.ai
John: The team behind 11.ai is, of course, ElevenLabs. They’re a company that has, in a relatively short time, established itself as a frontrunner in AI voice technology. Their tools for voice cloning and generating synthetic speech are known for their remarkable quality and emotional range. This deep expertise in audio AI naturally positions them to innovate in the voice assistant space. The development of 11.ai seems to be a strategic move to leverage their core strengths and expand their portfolio beyond voice generation tools into interactive AI applications. The individuals involved, as seen in some LinkedIn posts, are clearly passionate about pushing the boundaries of conversational AI and its practical applications. They describe 11.ai as an “experiment” but one with a clear vision: to demonstrate the potential of AI that doesn’t just talk, but *does*.
Lila: It’s always inspiring to see a company leverage its core strengths to build something new and potentially transformative. What about the community aspect? With a product in alpha, I imagine user feedback is gold. Is there an active community forming around 11.ai, or ways for early users to connect and share experiences?
John: Absolutely, user feedback is the lifeblood of any alpha program. While a dedicated, public community forum for 11.ai specifically might still be in its nascent stages given how new the announcement is, ElevenLabs already has existing communities around its other products, often found on platforms like Discord or Reddit (like the r/ElevenLabs subreddit where users are already discussing 11.ai). It’s highly probable they will establish specific channels for 11.ai testers to provide feedback, report bugs, and share use-cases. We’re already seeing initial reactions and discussions on platforms like LinkedIn, X (formerly Twitter), and YouTube, where tech enthusiasts and early adopters are sharing their first impressions and thoughts. For instance, the LinkedIn post by Axelle Malek describes it as feeling “like the movie ‘HER’,” which gives you a sense of the excitement and the kind of user experience they are aiming for. This early buzz and direct engagement with users is crucial for iterating on the product and building a user base that feels involved in its development.
Lila: That “movie ‘HER'” comparison is quite something! It sets a high bar for the level of natural interaction. So, the early sentiment seems quite positive and excited, even if it’s acknowledged as an early experiment?
John: Yes, the initial sentiment, based on the early online chatter and articles, is largely one of excitement and anticipation. There’s a recognition of ElevenLabs’ strong track record in voice AI, which lends credibility to this new venture. People are intrigued by the promise of a “voice-first AI personal assistant that supports MCP and is designed for real tasks.” The key differentiators – the quality of voice, the focus on actionable tasks, and the integration with productivity tools – are resonating with those who feel current voice assistants are somewhat limited. Of course, as with any alpha product, there’s also an understanding that it’s a work in progress. But the willingness of ElevenLabs to release it as a “proof of concept” and engage with the community for feedback is generally seen as a positive and transparent approach. The tech community loves to be part of the journey, especially for something that feels genuinely innovative.
Use-Cases & Future Outlook: What Can 11.ai Do For You?
John: The practical applications of 11.ai, even in its early stage, are quite compelling, focusing on “actionable productivity.” Primarily, we’re looking at **task management**. Imagine verbally telling 11.ai, “Create a task in Notion to finalize the Q3 report by next Friday and assign it to me,” and it just happens. This extends to tracking existing tasks or updating their status. Then there’s **research and information retrieval**, thanks to integrations like Perplexity. You could be working on a document and say, “11.ai, find me three recent articles on the impact of AI on journalism,” and get a quick, summarized response. **Communication and scheduling** are also key; think “11.ai, check my Google Calendar for availability next Tuesday afternoon and draft an email to Lila suggesting a meeting.” Beyond these, the real power lies in **workflow automation** – stringing together multiple actions. For example, “11.ai, when I receive an email with ‘invoice’ in the subject, save the attachment to my ‘Invoices’ folder in Google Drive and add a task to my to-do list to process it.”
Lila: Those examples really bring it to life! It’s like streamlining all those little digital housekeeping tasks that eat up so much time. Can you give me a scenario of how someone might use 11.ai throughout a typical workday?
John: Certainly. Let’s imagine a project manager, Sarah. She starts her day: “11.ai, what are my top priority tasks in Linear for today?” As she sips her coffee, 11.ai reads them out. Later, in a virtual meeting, a new action item comes up. Sarah quietly says, “11.ai, add a task to our ‘Project Phoenix’ board in Notion: ‘Investigate new marketing channels for H2 launch,’ and assign it to Mark, due next Wednesday.” Mid-morning, she needs to prepare for a client call: “11.ai, pull up the latest notes on the Acme Corp account from Slack and find recent news articles about their industry using Perplexity.” Before lunch, she might say, “11.ai, schedule a 30-minute follow-up call with John Doe for tomorrow at 2 PM via Google Calendar and send him an invite.” Throughout the day, she could use it to draft quick replies to messages, set reminders, or even log her work hours. The goal is to minimize context switching and keep her focused, with 11.ai acting as her verbal command center for various digital tools. It’s about “rapid task handling and real-time updates directly from discussions,” as one source puts it.
Lila: That sounds incredibly efficient. It’s definitely more than what Siri or Alexa can do in terms of work productivity. How do you see 11.ai evolving? What’s the future outlook for this kind of technology?
John: The future outlook is very promising, Lila. Right now, 11.ai is a prototype, showcasing core functionality with a select set of integrations. We can expect this list of integrations to grow significantly, encompassing a wider range of popular business and productivity applications. The “5,000+ voices” mentioned suggest a deep level of personalization will become standard. Beyond that, the AI’s understanding of context and nuance will likely improve, allowing for more complex, multi-turn conversations and more sophisticated task automation. Imagine 11.ai learning your preferences and work habits, proactively suggesting actions, or even being able to handle ambiguous requests more intelligently. There’s also the potential for more advanced capabilities, such as summarizing long documents or email threads on command, or even participating more actively in meetings by taking notes and identifying action items automatically. The long-term vision could be an AI assistant that is truly indispensable, seamlessly woven into the fabric of our digital lives, almost like the advanced AI assistants we see in science fiction – but grounded in practical, everyday productivity. The key will be maintaining user trust through robust security and privacy measures as these capabilities expand.
Competitor Comparison: How Does 11.ai Stack Up?
John: When we look at the competitive landscape, 11.ai is entering an interesting space. On one hand, you have established voice assistants like Amazon Alexa, Google Assistant, and Apple’s Siri. These are widespread but often criticized for their limitations in performing complex tasks or integrating deeply with third-party work applications. Their strengths lie more in smart home control, quick information retrieval, and basic personal organization. On the other hand, you have productivity tools and automation platforms like Zapier or IFTTT, which are powerful for connecting apps but typically require manual setup through a visual interface, not natural voice commands for on-the-fly task execution. There are also newer AI-powered agents and tools emerging, some focused on specific niches like meeting assistance or email management.
Lila: So, where does 11.ai fit in, and what makes it stand out from, say, Zapier Agents which also aim to automate tasks across apps?
John: That’s a good comparison. Tools like Zapier Agents are indeed moving towards letting AI manage workflows. The key differentiator for 11.ai, as positioned, is its **voice-first interface** combined with **actionable task execution through deep integrations**. While Zapier is incredibly powerful for pre-defined automations (zaps), 11.ai aims to allow for more dynamic, conversational task delegation. You’re not just triggering a pre-set workflow; you’re having a dialogue to get things done in real-time. The emphasis on high-quality, natural-sounding voice from ElevenLabs also aims to make the interaction more pleasant and intuitive than typical text-based or clunkier voice interfaces. Furthermore, the MCP architecture, designed for direct intervention in digital work processes, suggests a level of responsiveness and flexibility that might be different from trigger-action platforms. It’s about bringing the ease of voice to the complexity of multi-app workflows. The comparison to the movie ‘Her’ highlights this aspiration for a natural, almost personal interaction that goes beyond functional commands.
Lila: So, it’s the combination of that natural, high-quality voice interaction with the ability to actually *do* things in other apps that sets it apart? It’s less about setting up static automations and more about dynamic, in-the-moment delegation via voice?
John: Exactly. While setting up complex, recurring automations will likely still have its place, 11.ai is gunning for those ad-hoc tasks, the “Hey, can you quickly do X, Y, and Z for me?” moments that currently require you to manually jump between several apps. Think about managing your calendar, firing off a quick message on Slack, creating a task in Linear, or looking something up on Perplexity – 11.ai wants to be the single, voice-driven interface for all of that. It’s about reducing the friction of project management and enabling “rapid task handling” and “real-time updates directly from discussions.” The ultimate goal seems to be an assistant that understands your intent from natural language and then efficiently manipulates your digital tools on your behalf, almost like a human assistant would, but with the speed and consistency of AI. This focus on “actionable productivity” through a seamless voice experience is its core value proposition in a crowded market. It’s not just about understanding your voice; it’s about translating that voice into meaningful actions within your digital ecosystem.
Risks & Cautions: Navigating the New Frontier
John: As with any powerful new technology, especially one that interacts with personal and potentially sensitive data across multiple applications, there are inherent risks and cautions to consider. Firstly, **data privacy and security** are paramount. When you grant an AI assistant access to your email, calendar, project management tools, and communication platforms, you’re entrusting it with a significant amount of information. ElevenLabs will need to be extremely transparent about their data handling policies, encryption methods, and how they ensure that user data is protected from unauthorized access or breaches. Users will rightly want to know where their data is processed and stored, and who has access to it.
Lila: That’s a huge concern. If it’s connecting to my Slack and Google Calendar, I’d want to be very sure about security. What about the reliability of the assistant itself? Since it’s in alpha, I guess it might not always get things right?
John: You’re absolutely right to point that out, Lila. **Accuracy and reliability** are critical, especially for an “actionable” assistant. If 11.ai misunderstands a command and schedules a meeting for the wrong day, or assigns a task to the wrong person, or shares sensitive information inappropriately, the consequences could range from minor inconvenience to significant problems. In an alpha stage, users should expect some level of imperfection. That’s the nature of early software – it’s an opportunity to identify and fix these kinds. The platform will be learning and improving. There’s also the risk of **over-reliance**. As these tools become more capable, users might become overly dependent on them, potentially losing some of their own skills in managing tasks or information. And, of course, the nuances of human language mean there’s always a chance of misinterpretation, particularly with complex or ambiguous voice commands. Clear feedback mechanisms for correcting errors and refining requests will be essential.
Lila: So, early adopters should go in with a mindset of being testers, ready to report bugs and not expect perfection straight away. Is there anything else users should be mindful of?
John: Another aspect to consider is the **scope of permissions**. Users will need to carefully review what access they are granting 11.ai within each integrated application. It’s always good practice to grant the minimum necessary permissions for the functionality you need. There’s also the broader societal question about the impact of such advanced AI on jobs, though 11.ai is positioned more as an augmentation tool for individuals rather than a replacement. Finally, as the technology matures, understanding the **limitations of the AI** is important. While it might seem incredibly intelligent, it’s still an algorithm operating based on its training data and programming. It won’t have genuine understanding or consciousness in the human sense. Maintaining a degree of healthy skepticism and critical thinking when interacting with any AI, including 11.ai, is always advisable. Users should be active participants, understanding what the tool is doing and why, especially in these early stages of its development.
Expert Opinions & Analyses
John: The launch of 11.ai, even in its alpha stage, has certainly caught the attention of tech commentators and AI enthusiasts. The general consensus is one of cautious optimism and intrigue. Many experts acknowledge ElevenLabs’ strong reputation in voice synthesis as a significant asset. For instance, publications like ZDNet and MLQ.ai have highlighted its “voice-first” nature and its capability to handle “actionable tasks” and “workflow automation.” The integration with popular tools like Slack, Google Calendar, and Perplexity is frequently cited as a key strength, moving beyond the capabilities of standard voice assistants. The fact that it uses an architecture like MCP (Model-Controller-Periphery) to directly intervene in digital work processes is also seen as a sophisticated approach.
Lila: So, the experts are generally positive about the concept. Is there any skepticism or are there particular areas they are watching closely?
John: Yes, while the potential is recognized, there’s also a healthy dose of analytical caution. Some commentary, like the post on Metaverse Post, refers to 11.ai as a “prototype” and an “experiment.” This framing is important – it manages expectations and underscores that this is early-stage technology. Experts will be closely watching its real-world performance, particularly its reliability in understanding diverse commands and accurately executing tasks across different integrated platforms. The user experience – how natural and intuitive the voice interaction truly feels – will be a critical factor for adoption. Privacy and security implications, as we discussed, are also consistently raised as crucial areas that ElevenLabs will need to address robustly. There’s also the question of differentiation in an increasingly crowded AI assistant market. While voice-first and actionable task management are strong selling points, sustained innovation will be key. Some compare it to the “movie ‘HER'” which is a high aspiration, and experts will be judging how close it can actually get to that level of intuitive, almost human-like assistance.
Lila: It sounds like the tech world is saying, “This is very promising, ElevenLabs, show us what it can really do as it matures!” What about the developer perspective? Are they excited about potentially building on or integrating with 11.ai in the future?
John: While it’s still very early for third-party developer programs for 11.ai itself, the underlying principle of interconnected AI assistants is something developers are keenly interested in. If 11.ai eventually opens up an API or an SDK (Software Development Kit) for developers to create new “skills” or integrate more services, that could significantly expand its capabilities and ecosystem. The mention of “MCP” suggests a modular architecture that could potentially lend itself to such expansions. For now, the developer community is likely observing with interest, particularly those already working with ElevenLabs’ voice AI APIs for other applications. The excitement often stems from the potential to move beyond simple command-response interactions to more complex, context-aware conversational AI that can genuinely augment human productivity. The success of the initial integrations will be a key indicator for potential future developer engagement. An AI assistant that can reliably orchestrate tasks across multiple apps is a powerful concept, and developers are always looking for robust platforms to build upon.
Latest News & Roadmap: What’s Next for 11.ai?
John: The most significant recent news is, of course, the launch of the 11.ai alpha program itself, which seems to have happened around late June 2025, according to some reports. This unveiling marks ElevenLabs’ official entry into the AI personal assistant market, expanding from their core business of voice synthesis. Key announcements emphasize its “voice-first” approach, its ability to take action via integrations with tools like Perplexity, Google Calendar, Slack, Notion, and Linear, and its use of an MCP-like architecture. The availability of over 5,000 voices for personalization is also a notable feature highlighted in early information. The current phase is described as a “proof of concept” or an “experiment,” indicating that ElevenLabs is focused on gathering user feedback to refine the product.
Lila: So, the big news is that it’s here in alpha! Is there any indication of what features or improvements might be on their immediate roadmap, say, for the next few months as they gather this feedback?
John: Official, detailed roadmaps for alpha products are often kept flexible, as development priorities can shift rapidly based on user feedback. However, we can infer some likely directions. Firstly, **expanding integrations** will almost certainly be a priority. The current list (Slack, Google Calendar, Perplexity, Notion, Linear) is a strong start, but users will undoubtedly request connections to many other popular productivity, communication, and social media tools. Secondly, **improving the natural language understanding (NLU)** and the contextual awareness of the assistant will be an ongoing effort. This means making 11.ai better at understanding complex, nuanced, or even ambiguous commands, and remembering context from previous interactions. Thirdly, **enhancing reliability and accuracy** in task execution will be critical. As more users test it, identifying and fixing bugs or points of failure in the workflow automation will be paramount. We might also see refinements in the user interface or interaction model based on what testers find most intuitive or challenging.
Lila: That makes sense – more tools, smarter understanding, and making sure it actually works reliably. What about wider availability? Any hints on when it might move from alpha to beta, or even a full release?
John: There’s no concrete timeline publicly available for moving out of alpha, then to beta, and eventually to a full release. This is typical for such ambitious AI projects. The duration of the alpha phase will largely depend on the volume and nature of the feedback received, how quickly critical issues can be addressed, and how well the core functionalities perform in diverse real-world scenarios. ElevenLabs will want to ensure a certain level of stability, usability, and value before broadening access. Users can likely anticipate iterative updates throughout the alpha and any subsequent beta phase. The company will be looking for signals that 11.ai is consistently delivering on its promise of “actionable productivity” and providing a genuinely superior user experience. Keeping an eye on ElevenLabs’ official announcements will be the best way to stay informed about its progress towards wider availability. For now, the focus is squarely on learning from these initial users and building a solid foundation.
Frequently Asked Questions (FAQ)
Lila: John, people are bound to have a lot of questions about 11.ai. Maybe we can cover some of the most common ones?
John: An excellent idea, Lila. Let’s tackle a few.
Lila: Okay, first up: For someone just hearing about it, **what exactly *is* 11.ai in simple terms?**
John: In simple terms, 11.ai is a new type of personal assistant for your computer or devices, created by ElevenLabs. You talk to it using your voice, and it’s designed to not just answer questions, but to actually *do* things for you, like manage your tasks, schedule meetings in your calendar, help with research by connecting to tools like Perplexity, and automate parts of your digital workflow across different apps.
Lila: And **who is the company behind 11.ai?**
John: 11.ai is developed by ElevenLabs. They are a well-known AI research company famous for creating very realistic and natural-sounding AI voices. They’re now using their expertise in voice technology to build this intelligent assistant.
Lila: This is a common one I’ve seen: **How is 11.ai different from existing voice assistants like Siri or Alexa?**
John: The main difference lies in its focus on “actionable productivity” and deep workflow integration. While Siri and Alexa are great for setting timers, playing music, or answering general knowledge questions, 11.ai is designed to perform more complex tasks directly within your work-related applications (like Slack, Google Calendar, Notion, Linear). It aims to understand more complex instructions and execute multi-step actions that help you manage your professional life, essentially acting as a productivity-focused extension of yourself.
Lila: You mentioned “MCP” earlier. **What is MCP in the context of 11.ai?**
John: MCP is believed to stand for Model-Controller-Periphery. It’s an architectural framework. The **Model** refers to the AI (like large language models and speech processing) that understands your request. The **Controller** is the decision-making part that figures out what actions to take. The **Periphery** refers to the connections or integrations that allow 11.ai to interact with your other software and services (the “peripherals”). This structure enables 11.ai to directly intervene and manage tasks within your digital tools.
Lila: And speaking of those tools, **what are some of the key tools 11.ai can currently integrate with?**
John: Based on initial announcements, 11.ai can integrate with several popular productivity tools. These include Slack for communication, Google Calendar for scheduling, Perplexity for AI-powered research, Notion for notes and databases, and Linear for issue tracking and project management. The list is expected to grow as the platform develops.
Lila: That’s a good starting list! **Is 11.ai free to use?**
John: Currently, 11.ai is in an alpha testing phase, and reports indicate that it is free to try for those accepted into the program. This is common for alpha software, as the company’s goal is to gather feedback. Future pricing models for a commercial release haven’t been announced yet.
Lila: Lastly, if people are excited and want to learn more, **where can they find more information or potentially sign up to try 11.ai?**
John: The best places to look for more information or opportunities to join the alpha program would be the official ElevenLabs website (elevenlabs.io) and any dedicated product pages or announcements they release for 11.ai. Their official social media channels, like LinkedIn and X (Twitter), are also good sources for the latest updates.
Related Links
John: For our readers who want to dive deeper, here are a few resources:
- ElevenLabs Official Website: The primary source for company information and potential news on 11.ai.
- MLQ.ai Article: Provides an overview of the 11.ai launch and its capabilities.
- ZDNet Article: Discusses 11.ai’s ability to take action and its free trial availability.
- ElevenLabs LinkedIn Announcement: Official post about 11.ai.
- Metaverse Post Article: Covers the introduction of 11.ai and its features.
John: So, Lila, 11.ai certainly represents an exciting step forward in voice-first AI assistance. It’s early days, but the ambition to create a truly actionable, integrated assistant is clear. ElevenLabs is leveraging its formidable expertise in voice AI to tackle a real challenge: making our interaction with technology more natural and productive.
Lila: It really does, John! The idea of just *talking* to my apps and having them work together seamlessly sounds like it could genuinely change how we manage our digital lives. I’m definitely going to be keeping a close eye on 11.ai’s development. It feels like we’re on the cusp of assistants becoming true partners rather than just command-takers.
John: Well said. It’s a space full of potential. As always, readers should remember that new technologies, especially in alpha stages, evolve rapidly. It’s important to do your own research (DYOR) and understand the capabilities and limitations before integrating any new tool deeply into your workflows, particularly concerning data privacy and security.