Evernote v11 AI: Redefining Note‑Taking with Semantic Search, Assistant, and Meeting Notes

Author: Boxu Li**** at Macaron

Introduction:

Evernote’s latest version 11 marks its most significant update in years, transforming the veteran note-taking app into an AI-powered productivity hub[1]. With Evernote v11 AI, the platform introduces three headline features – Semantic Search, an AI Assistant, and AI Meeting Notes – designed to save time and augment how users capture and retrieve information. This comprehensive overview examines Evernote v11’s AI capabilities and how they stack up against Notion AI, Microsoft 365 Copilot, and Google Workspace Duet AI. We’ll also analyze pricing, data security, and user experience, and discuss use cases for individuals, teams, and organizations. (Keywords: Evernote v11 AI, semantic search, AI note-taking apps, AI assistant for meetings.)

Evernote v11: A Second Brain with Built-in AI Intelligence

Evernote v11 positions itself as an “AI-first” note-taking app under new ownership (Bending Spoons), aiming to “redefine the role of note-taking tools in the age of AI”[2][3]. The update delivers a modernized interface and over 200 improvements, but the AI features take center stage[4][5]. In essence, Evernote now behaves like a smart second brain – understanding natural language queries, generating content, and automatically organizing your notes. Below is an overview of each major AI capability:

AI Assistant: Evernote’s Built-in ChatGPT

Evernote’s AI Assistant is essentially “ChatGPT inside of Evernote”[6] – a conversational helper that lives in a dedicated chat panel. Developed in partnership with OpenAI, the assistant uses cutting-edge large language models to understand instructions and content in context[7]. Users can ask the assistant anything from summarizing or editing a note to brainstorming ideas or creating new content, all without leaving Evernote[8][9]. For example, you might ask “Summarize my project notes and draft an email update”, and the assistant will generate the summary and action items directly in your notebook[10].

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Crucially, the AI Assistant isn’t limited to your existing notes – it can also perform in-app web searches to pull in external information[11][12]. This means Evernote can serve as an all-in-one workspace where you research a topic online and integrate the findings into your notes via the assistant[13][14]. Early testers have demonstrated creative uses, like converting meeting notes into a LinkedIn post or even translating code from one language to another using the assistant[15][16]. Essentially, the AI Assistant can generate, organize, and act on content – you can ask it to draft text, tag and restructure notes, or execute actions like moving a note to a different notebook[17]. Evernote hints at even more automation to come (e.g. automatic tagging and batch note management in future updates[18]).

From a user experience standpoint, the assistant appears as a chat sidebar where you type requests and receive results with references. It can cite relevant notes as sources when answering questions about your knowledge base[19][20], helping you trace where information came from. The tone and capabilities are similar to general-purpose AI chats, but uniquely blended with your personal content. Federico Simionato, Evernote’s Product Lead, notes this integration allows users to “search and retrieve content, modify or generate content like summaries and action items, and execute actions across the account” in a fluid conversational way[17]. In short, the assistant turns Evernote into an interactive, AI-driven workspace rather than a static archive of notes.

Semantic Search: Finding Notes by Meaning, Not Keywords

Many Evernote power users have accumulated thousands of notes over the years, and finding information quickly is paramount. Evernote v11’s new Semantic Search finally delivers a feature users “have been waiting a decade for”[21] – the ability to search by meaning and natural language, not just exact keywords. This in-house AI search engine interprets the context of your query and surfaces relevant notes even if specific keywords are absent[22].

For example, searching “UK vacations” might return notes titled “London Trip” or “Edinburgh Trip,” recognizing those are semantically related to the concept of a UK vacation[23]. It can even extract details from notes – such as a flight confirmation number – if you ask a question like “When is my flight to NYC?”[23]. In other words, Semantic Search adds a layer of understanding on top of Evernote’s traditional indexing, so you can retrieve information based on ideas and attributes contained in your notes rather than the exact wording.

Beta users report that the new semantic search is “way better than the existing search, by a mile” at finding what they need[24]. A query now yields an instant answer (if possible) along with relevant notes and even snippets showing the answer in context[25]. In an example shared by a tester, a natural question in the search bar produced an answer plus a list of related notes – all within the search interface[25]. This resembles an AI Q&A experience akin to modern search engines, but applied to your personal or team knowledge base.

Notably, Evernote’s Semantic Search runs entirely on Evernote’s servers using an internal model, not OpenAI. The company emphasizes that your note data is not sent to third-party AI for semantic queries[26][27]. Evernote essentially built a domain-specific semantic index of your notes (likely via embeddings or similar techniques) to enable this feature. From a privacy perspective, this means finding information in your notes by meaning does not expose your content externally – a design choice likely meant to reassure users who are wary of cloud AI services.

The benefit of Semantic Search is especially evident for users who “forgot the name of a note” or need to retrieve something based on memory fragments[28]. Rather than guessing which keywords you used, you can describe it in plain language. For longtime Evernote users with a “second brain” of notes, this capability can dramatically improve how quickly knowledge is resurfaced. It turns Evernote into a more context-aware archive – closer to having an intelligent research assistant comb through your notes for answers.

AI Meeting Notes: Automatic Transcripts and Summaries

Evernote v11 also addresses a common pain point: capturing and summarizing meeting information. The new AI Meeting Notes feature builds on Evernote’s existing audio recording and transcription capabilities, but supercharges them with real-time AI processing[29][30]. Users can record a meeting (in-person via microphone or remote via a browser integration) and let Evernote automatically generate a transcript and summary, complete with speaker identification[31][29].

In practice, AI Meeting Notes acts like a virtual minute-taker. It will transcribe the conversation (using Evernote’s cloud speech recognition) and then produce an organized summary of key points and action items almost immediately after the meeting ends[30][31]. Evernote’s prior AI Transcribe (introduced in 2024) could turn audio into text, but the new version 11 goes further by structuring that text into digestible notes with identified speakers and highlights[30]. This means you can finish a meeting and have a clean set of notes ready to share, without the frantic typing or later manual summarization.

Evernote v11 AI Meeting Notes in action: recording a meeting via the app and generating an AI-written summary with speaker labels (conceptual example).

The Meeting Notes feature integrates with Evernote’s calendar and note system. You can start a recording from a note (e.g. a meeting template) and the transcript will be saved into that note along with the summary. Evernote’s teaser shows the interface allowing users to choose “Remote meeting” or “In-person meeting” modes, then record the session[32][33]. For remote meetings, Evernote can capture the audio from a chosen web conferencing tab (currently supported via a Chrome/Edge browser extension)[34]. This is similar to dedicated AI meeting assistants like Otter.ai or Fireflies, but now built directly into Evernote’s app.

There are still some limitations: Evernote’s recording duration is currently capped (about 1 hour or 100 MB per meeting, as per existing plan limits)[35]. Power users note that this may not cover longer workshops or lectures, expressing hope that the limit will increase over time[35]. Additionally, while speaker differentiation is supported (e.g. Speaker 1, Speaker 2), the system doesn’t actually know the participants’ identities – it doesn’t name them, it just separates by voice. This is done without sending data to outside services; like transcription before, it runs via Evernote’s service (likely using an AI model but under Evernote’s control).

Overall, AI Meeting Notes can be a boon for both individual users and teams. No more losing focus to take notes – you can rely on Evernote to capture the discussion verbatim, then read the concise summary to review decisions and action items. Evernote is essentially offering an integrated meeting assistant, similar in goal to Zoom’s AI summaries or Google Meet’s new Duet AI notes, but in a cross-platform, app-agnostic way (any meeting, any platform, as long as you can record it). For users already managing projects and notes in Evernote, keeping meeting records in the same system with automated processing is a big productivity win.

User Experience and Productivity Impact

Integrating AI into note-taking can profoundly change the user experience. Evernote v11’s AI features were crafted to be “integrated directly into your existing workflows”, not separate tools[80][81]. Early feedback from beta users indicates that these additions do accelerate common workflows. For example, one user reported: “the AI-powered improvements are very welcome, as they speed up my workflow”, highlighting Evernote’s simplicity and cross-platform nature for business use[81]. Having a chatbot in Evernote that can retrieve a note or summarize it means less time manually searching or scrolling. Likewise, being able to generate a quick draft or meeting summary right where your notes live saves the cognitive burden of switching to external apps or services.

The flow in Evernote v11 is designed to be intuitive: you can hit Ctrl+Q (for instance) to jump to the AI Assistant chat, ask a question in natural language, and get results with context. If you perform a normal search, the app now gives you semantic suggestions and answers inline[25] – essentially turning the search bar into a Q&A interface for your notes. This blurs the line between searching and asking, which for the user means faster access to information. In practice, it’s like having a smart librarian for your second brain, rather than manually constructing search queries and filters.

When it comes to content creation, users no longer face the blank page alone. Need to draft a blog outline or a project plan? Evernote’s assistant can generate a first pass which you can then refine. This is similar to Notion’s AI which many have used for drafting social media posts or brainstorming. The integration means you don’t have to copy-paste from ChatGPT into your notes; the AI can reference your notes while generating text. For instance, you could write “Use notes in Project X notebook to give me a summary of our research findings,” and the assistant will pull the relevant points[82]. That is a powerful workflow improvement for any kind of research or writing tasks.

Meeting productivity is another experiential leap. Consider the before-and-after: previously, to capture a meeting, you might audio-record it, then later run a transcription service, then read through to make manual notes. With Evernote v11, you hit record at the start of the meeting, and by the end you have a neatly summarized note. This allows meeting participants to stay engaged in conversation rather than note-taking[83][84]. Notion AI Meeting Notes and Microsoft Teams intelligent recap have similar goals – to free you from the minutiae of documentation and let AI do that job. One can imagine small teams in particular benefiting: instead of assigning someone as the meeting scribe, let Evernote handle it and everyone can focus on discussing. After the meeting, the team can quickly review the AI-generated minutes, correct any nuance if needed, and share them. It reduces friction and ensures nothing falls through the cracks (action items are captured automatically).

Of course, the quality of AI outputs matters for user experience. Evernote claims “accurate summaries” for meeting notes[85] and presumably has fine-tuned the assistant for typical note content. However, users will still need to verify and edit AI outputs, especially for critical or creative work – a fact even Microsoft acknowledges (“Copilot generates a draft… you’ll need to verify and modify”[86]). So, while Evernote’s AI can draft an email or find a note, the user remains the editor and decision-maker. The best experiences reported are when AI handles the heavy lifting of first-draft or information retrieval, and the user then refines the results.

In terms of UI design, Evernote v11 sports a refreshed look and branding[87], but longtime users will still find a familiar left sidebar of notebooks and notes list. The addition of AI didn’t drastically alter the UI – rather, it added panels and options when needed (e.g., an “Ask AI” button or the new search dropdown with AI results). Evernote also introduced an AI settings dashboard for transparency and control[88], showing a commitment to user-centric design (letting people opt out or see what’s enabled easily). The responsiveness and performance improvements under the hood mean the AI features don’t feel bolted on – as Simionato noted, this update came after years of foundational work to improve reliability and fix bugs[5]. A smooth, fast app is key because AI features won’t impress if the app is sluggish or crashes (Evernote had a reputation for bloat in the past). Early signals are positive on this front, with the Evernote team emphasizing speed/stability in v11[89].

It’s also interesting to consider cross-device experience. Evernote’s AI features are rolling out on desktop and web first, with mobile support to follow soon[90][57]. This phased release is likely due to the complexity of implementing the chat UI and real-time transcription on mobile. But once available, imagine speaking into your phone’s Evernote app during an in-person interview and getting a summary by the time you reach your desk – that could be a game-changer for journalists or salespeople on the go. Notion’s mobile AI features are also catching up (their chat and meeting notes currently require desktop for full functionality[91][92]). Microsoft and Google’s AI are accessible on mobile mainly through their app equivalents (e.g., mobile Outlook’s “help me write” or mobile Docs “help me draft”), though these are still evolving. Evernote’s cross-platform nature (available on Windows, Mac, Web, iOS, Android) may give it an edge in consistency of note-centric AI experience wherever you are.

One should note that not all users are immediately on board with AI. There is a segment of users who have expressed skepticism or reluctance about AI features – for example, some Evernote users said “I don't want anything to do with ChatGPT. Anything.”[93]. Evernote’s response has been to respect that stance by keeping features opt-in. Over time, as these tools prove their value (and their safety), more users may warm up to using them. The real test of user experience will be: do Evernote’s AI features actually feel like a trustworthy productivity partner or more like a gimmick? Based on early use cases and feedback, it leans toward the former – many are already finding practical time-savers, and Evernote’s marketing frames the AI as “your powerful companion”[7] rather than a novelty.

Use Cases and Adoption Strategies for Power Users, Teams, and Companies

Evernote v11’s AI capabilities open up new use cases across different user segments, from individual “power users” to small teams and tech-forward enterprises. Here we explore how each group can leverage these features and what adoption might look like:

Individual Power Users and Professionals

Power users – think writers, researchers, entrepreneurs, students – have long used Evernote as an extension of their brain. For them, v11’s AI can be a personal game-changer. The Semantic Search means an academic, for instance, can find references in years of research notes by asking natural questions (“find my notes on 19th-century trade routes in Asia”) and Evernote will surface the relevant entries even if specific keywords differ[23]. This saves time that would otherwise be spent combing through notebooks or remembering tags.

The AI Assistant becomes like a personal research assistant or editor. A writer could draft a chapter summary by prompting the assistant, or ask it to generate ideas for an article based on snippets of notes they’ve gathered. Since the assistant can incorporate note content, you could feed it your raw thoughts and then ask “Organize these points into a coherent outline”. The assistant can also help manage the Evernote account itself: for example, “Show me notes related to tax documents and tag them ‘2025 taxes’” – a conceivable command given Evernote’s notion of action-oriented AI[94]. Early testers mentioned actions like adding tags or moving notes via the chat[94][9], which is a boon for those who use Evernote heavily and need to tidy or refactor their second brain.

Creative users and freelancers can use AI Meeting Notes in unconventional ways too. For example, a journalist might record an interview (with permission) and get an immediate transcript summary to identify the key quotes. A freelance consultant could record client meetings or brainstorming sessions and rely on Evernote to produce the notes to send the client afterward (increasing professionalism with minimal extra effort). For a student, recording lectures and getting summaries could vastly improve study efficiency – you can pay attention to the lecture knowing Evernote will capture it and highlight the important points. The one-hour limit might mean long lectures need to be broken up, but it’s still useful for typical class sessions or study group meetings.

Adoption strategy for individuals is straightforward since there’s low friction: Evernote is offering these features even on Free plans, so many will try them out of curiosity. The key is for Evernote to educate users on what to do with the AI (beyond a flashy demo). Evernote might share templates or examples: e.g., how to use the AI Assistant to plan a trip itinerary by querying notes and the web, or how to automate weekly task summaries. Given the enthusiasm on the Evernote user forum and communities, power users will likely share tips and workflows once v11 is fully released.

One possible concern for individuals is trust and habit: those who have developed robust manual systems (like detailed tagging, manual note linking, etc.) may be hesitant to rely on AI initially. Evernote’s opt-in approach lets them ease in – maybe they start by using semantic search occasionally, then gradually try the assistant for small tasks. The learning curve should be gentle for anyone familiar with consumer AI tools like ChatGPT.

Small Teams and Collaborative Workgroups

Small teams – startups, project teams, or departmental groups – can harness Evernote v11 AI as a lightweight collaborative knowledge base with intelligence built-in. Evernote Teams (formerly Evernote Business) allows shared notebooks, and now with Semantic Search, a team member can query the collective notes and instantly get answers or find who documented what. This addresses the classic problem of “tribal knowledge” in teams: important info is buried in someone’s notes, but now AI can help surface it so the whole team benefits. Notion has been popular for this use-case, but an Evernote advantage is simplicity – you don’t need to build a complex workspace structure; you can just create notes and rely on search to retrieve information.

For team meetings, Evernote’s AI Meeting Notes means no one needs to play the note-taker role. Teams can rotate who hits “record” in Evernote, and everyone gets the summary. The action items identified can be easily converted into Evernote Tasks (Evernote has a tasks feature) or followed up. Even if one or two members couldn’t attend, they have a reliable summary. This fosters inclusivity and continuity in small teams – decisions are less likely to be lost or miscommunicated. Competing products like Otter.ai also do this, but having it integrated into the same app where the team’s other notes and documents live is convenient.

Evernote’s AI Assistant can also facilitate team brainstorming and planning. In a shared notebook, a team could have a running “chat” with the assistant to, say, generate ideas for a marketing campaign using their existing notes on customer research. It’s like having an AI brainstorming session where all the team’s prior knowledge is accessible to the AI. Microsoft Copilot offers something akin to this with their 365 Chat (which can combine info from multiple sources to answer queries[55]), but again, that’s available only if a company pays big money. Evernote gives small teams on a budget a taste of that ability – e.g., a startup could use Evernote to store meeting notes, competitor info, design drafts, and then ask the AI “Summarize what we learned from user testing and suggest key features to focus on.” The answer, drawn from their actual notes, could help drive decision-making in the next meeting.

For adoption, small teams will weigh Evernote v11 AI against alternatives like Notion or simply using Google Docs with maybe an external AI. Evernote needs to prove that its all-in-one solution (notes + AI) is easier and more effective than piecemeal approaches. One strategy might be to encourage a pilot: a team could try Evernote Teams for a project and see how AI features improve their workflow. Because all members can use the AI (no extra cost per seat), there’s no internal friction about licensing. The team just has to be trained on best practices (ensuring everyone knows how to trigger the AI assistant or search effectively). Given that one beta user declared Evernote “one of the best note-taking apps for business use” due to its simplicity and speed[95], small teams that value those traits may find Evernote a better cultural fit than more complex tools.

Evernote will also need to address data governance questions for teams: While individuals might not worry, a small business will ask “Is our data safe in Evernote’s AI?” Evernote’s assurances (no training on your data, content is private[36]) and enterprise-grade security features (like data encryption, SSO for Enterprise, etc.) will be important to highlight. In other words, to win teams, Evernote not only has to deliver productivity gains, but also pass the IT/security sniff test, even at a small scale.

Tech-Forward Companies and Enterprises

Larger organizations and tech-forward companies are already exploring AI productivity tools – many will pilot Microsoft Copilot or Google Duet if they are in those ecosystems. Where does that leave Evernote? For enterprise adoption, Evernote faces an uphill battle because it’s not the incumbent platform. However, Evernote can find a niche in departments or use-cases that the big suites don’t serve well. For example, a creative team at a company that uses Microsoft 365 might still choose Evernote for its research and ideation work, if they feel Evernote’s interface and AI better support free-form thinking. Or consider cross-functional projects where not everyone has access to the same enterprise tools (e.g., external partners): an Evernote shared space could act as a neutral ground with AI-enhanced knowledge sharing.

Tech-forward companies might also consider Evernote Enterprise (if Bending Spoons continues offering it) for specific knowledge management needs. In the past, some enterprises used Evernote Business for things like field research collection or as a digital lab notebook system. With AI, those use cases expand – e.g., a consulting firm could use Evernote to accumulate case study notes, and consultants could query the semantic search to quickly find relevant past insights when preparing a new proposal. The adoption strategy here would be to start with a specific department or workflow that isn’t fully optimized by existing tools. Evernote could be introduced as a pilot in, say, the R&D department for technical notes and meeting recordings. If it shows clear time savings (e.g., engineers spend less time writing reports because AI drafts them from meeting notes), it could then scale to similar departments.

However, enterprises will be very sensitive to compliance, data residency, and integration. Evernote will need to provide answers around encryption, the location of AI processing, and assurances like GDPR compliance – especially since Bending Spoons (Evernote’s owner) is based in Europe, some EU clients might see that as a positive for data protection. The Evernote team explicitly mentions “EU data-residency options” as something being rolled out (likely for their Enterprise offering)[96], which shows they are gearing up to meet corporate requirements too.

For companies already investing in Microsoft or Google’s AI, Evernote’s pitch must be differentiation. One angle is knowledge longevity and portability. Evernote has always championed that your data is yours and you can export it[97]. A company might trust Evernote as an external system of record for certain knowledge, independent of their email/docs system. The AI features then become a bonus that that knowledge is more accessible and usable. Another angle is speed of innovation: Evernote can roll out features faster than large vendors – for instance, Evernote had semantic search deployed ahead of Google releasing something similar for their own Drive content. A tech-forward company might use Evernote in the interim to get these capabilities now, rather than waiting for their big provider’s roadmap.

In reality, Evernote v11 AI will likely see its strongest enterprise use in tech-savvy small-to-mid companies and specific power-user teams in larger companies. The broad enterprise may standardize on the big suites for AI due to bundle convenience. But in the diverse landscape of productivity tools, Evernote’s renaissance with AI can attract those who want a more focused, nimble solution. We see similar patterns with Notion being adopted in many startups and even some Fortune 500 teams despite SharePoint existing – it’s about the user experience and flexibility.

Conclusion: Evernote’s AI Evolution and the Road Ahead

Evernote v11’s AI features – Semantic Search, AI Assistant, and AI Meeting Notes – mark a pivotal evolution for a product that was once synonymous with digital note-taking. By infusing modern AI capabilities, Evernote is aligning itself with the future of work where information is instantly accessible and workflows are augmented by intelligent assistants. This transformation brings Evernote into direct comparison with offerings from Notion and the tech giants, and in many ways Evernote holds its own:

It offers powerful AI-driven search and assistance to all users (lowering the barrier to entry compared to pricey competitors)[56][71].
It has a privacy-first stance that will resonate with users concerned about who is training on their data[36][40].
It remains true to its core strength – being a user-friendly, cross-platform note organizer – now supercharged with intelligence to boost productivity[95].

For existing Evernote users, v11 promises to “level up your second brain” as the official tagline suggests[98]. Early signals indicate features like semantic search were indeed long-awaited improvements that can re-energize how people use Evernote[99][22]. Lapsed users disenchanted by Evernote’s past stagnation might find these updates worth a second look. And new users, drawn by the allure of AI note-taking, will be critical for Evernote to grow again in a competitive market.

Challenges remain. Evernote must ensure flawless execution – AI features that lag or err too often could frustrate users rather than help. It also needs to communicate clearly the best use cases so users integrate these tools into their routines (the value should be evident, e.g., “Evernote saves me an hour every day by summarizing my meetings and organizing my notes”). Additionally, Evernote’s decision to roll this out to free users is generous but will need careful management of usage levels and converting those free users into paying customers for sustainability.

On a strategic level, Evernote is effectively doubling down on being the AI-powered note app at a time when bigger players are making their whole suites AI-powered. This focus can be a strength if Evernote becomes known as the specialist that does notes + AI really well (in the way that, say, Figma thrived even as Adobe had broader design tools, by being the best in its niche). The note-taking app landscape now has a new baseline: simple text storage is not enough – users will expect their notes to be searchable by meaning, their apps to offer writing help, and their meeting notes to write themselves. Evernote is helping set this new bar.

In the broader context of digital productivity, Evernote v11 AI reflects a shift from mere information storage to information insight. It’s not just where you keep your thoughts, but a partner that actively surfaces and refines your thoughts. Whether you’re an executive distilling strategy points, a student studying smarter, or a team collaborating creatively, there’s potential for significant efficiency gains. The coming months will likely bring real-world stories of how Evernote’s AI is used – positive signals (or lack thereof) in user growth and retention will tell us if Evernote’s bold update is paying off.

To conclude, Evernote’s venture into AI is both a catch-up and a leapfrog: catching up to rivals that already integrated AI, and leapfrogging in areas like inclusive access and semantic note search. It has repositioned itself as a relevant, even cutting-edge player in the productivity space. If Evernote can continue innovating (e.g., improving AI accuracy, adding integrations, increasing limits as demanded) while nurturing trust, it stands a chance to reclaim its tagline of being an “external brain” – now smarter and faster than ever before. As one tech reviewer put it, this could make Evernote v11 “the most powerful and robust version of Evernote ever”[100]. For users and teams seeking an AI-enhanced note-taking experience in 2025, Evernote v11 has made a compelling case to be on the consideration list.

Evernote – “Work smarter with Evernote AI features” (official page)[7][36]
Evernote Help – “Evernote’s AI Features — FAQ”[56][68]
TechRadar – “Evernote v11 includes AI Assistant, Semantic Search, and AI-powered meeting notes”[17][23]
Taming The Trunk (Evernote community blog) – “First look at Evernote AI Assistant and Semantic Search”[26][27]
TechRadar – “Evernote unveils its biggest update in five years” (Sead Fadilpašić)[101]
Reddit (r/Evernote) – User feedback on v11 AI features and opt-out[42][81]
SecurityOnline – “Evernote Relaunches as AI-First Note App” (summarizing Evernote v11)[102][22]
Notion Blog – “Introducing Notion AI for Work”[45][61]
eWeek – “Notion AI for Work… at $20/user, all-in-one pricing”[54][48]
Microsoft – Copilot pricing and plans (Microsoft 365)[62]
Google via GPT.Space – Duet AI pricing $30/user[66]
Evernote Help – “Updated Pricing… introducing AI Search” (Feb 2025)[69][58]
Engadget – Evernote’s biggest update since 2020 goes all-in on AI (Igor Bonifacic via Yahoo)[71]
Engadget – details on rollout: desktop first, mobile later[90]
eWeek – “New Solution to AI Work Problem – Notion AI for Work”[47][103]

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