Deta’s new app, Surf, cuts across an AI-assisted browser-station and a manually-sourced notebook and plants itself in the center of this mob as a research workspace that thinks like an assistant but acts like a document editor. Rather than making users jump between a chat window and a regular browser or notes app, Surf does the stitching of workspaces for them, aiming at students, analysts, and anyone that has to deal with lots of tabs and PDFs.
What Surf Aims to Fix in Research and Note-Taking Workflows
It’s probably worth it for AI browsing tools to sprint to answers even if they don’t leave much of a paper trail. On the other hand, note-taking apps conserve process without understanding much of the web context you are working in. In research studies from companies like McKinsey and IDC, we have heard for a long time about the cost of this disconnect—with knowledge workers reported spending a fifth or more of their work week searching for information and reassembling context across tools.
Surf tackles the gap through combining browsing, summarization, and structured note-making into a single tool. I’m not just reaching towards results, I’m trying to jump directly into an editable, living document that captures the sources you’ve opened and the questions you’re asking—even if it doesn’t mean copying and pasting everything you might learn by hand.
How the Hybrid Browser-Notebook Approach in Surf Works
Surf is a browser that works like a notebook. You can open URLs, PDFs, and even YouTube videos, then ask the built-in assistant to read the content on screen. The app will be able to create a basic “gist” of a subject from your prompt and then write the response in an organized report in what looks very similar to a Notion document that you can edit, annotate, or expand however you’d like.
Context is central. You can point to several open tabs in a single query, instructing the assistant where it should look. Compare a journal article, a company blog, and a lecture video: Surf can knit the materials together as a lexically cross-referenced summary, pulling significant insights out of them and then attributing your understanding back to the tab from which any given insight came.
Surf can also produce code snippets, which are handy for creating small interactive charts or utilities that live inside your notebook. Assistant results are drop-in blocks, so your research, visuals, and citations stay wrapped in their source’s context instead of pinging around between apps.
Local-first design is another hallmark. Surf stores notebook data locally and uses offline capabilities, together with a web-like interface for interaction, as a bridge rather than a requirement. That’s a concrete win for travelers, campus users on dodgy Wi‑Fi, and anyone who favors privacy by default.
Where Surf Differs From NotebookLM and AI Browsers
Google’s NotebookLM introduced the concept of basing a notebook on your own sources and posing questions to that corpus. Surf incorporates this same motivation, but sticks it into a browser shell so sourcing and reasoning over it are done in one flow. That eliminates a frequent point of friction—hopping out to the web, only to drag content back into your notebook later.
Competitors to AI browsers like Perplexity’s Comet (has tabs with assistants; pages are summarized by AI), The Browser Company’s Dia, and experimental builds of Opera have played around with tab-aware assistants/page summaries. Deta’s pitch is that so many of these tools remain focused on the web as a playground for clicking automation, when researchers want and need a workspace they can reconfigure. In practice, that makes it so that Surf prefers editing documents, stateful notebooks, and on-device storage over ephemeral chat output.
The design philosophy also flies in the face of read-only AI interfaces. Without the ability to revise, reorganize, and cite within the same surface where the AI is reasoning, says Deta’s team, users end up slowed down on serious work. Surf takes a notebook-first position of keeping the human in the loop, yet still providing the assistant full access to open, curated materials.
Roadmap, Business Model, and Funding for Deta Surf
The beta version of Surf is free, and image generation is on the roadmap.
Deta is contemplating a premium tier that would include cloud backup, collaboration, and multi-device clients—natural upgrades if the app turned into a daily research hub for teams and classrooms.
The company, which was founded in 2019, initially dabbled with developing an “infinite canvas” operating system before making the pivot to AI-native browsing. It raised a $3.6 million seed round led by Crane Venture Partners in 2023, and then received an extra $500,000 from new and existing investors—all small but targeted funding befitting of a product that’s especially focused on local execution and tight grips on user data.
Privacy-minded design could have commercial relevance. Tools that reduce the amount of data that is generated—or “data exhaust”—as well as ones with offline modes, may get more institutional takers as regulators, alongside groups like the Electronic Frontier Foundation, continue to pore over data retention and model training practices—particularly in education and research environments where sensitive materials are commonplace.
Why Surf’s Approach to AI Research Workflows Matters
Surf’s bet is simple: if the browser knows what you’re working on and the notebook knows where its content originated, you’ll do better research faster. Imagine a student constructing a literature review: open five papers plus a recorded lecture, ask Surf to report methods and limitations, create a comparison chart, then fold all of these in with their sources into an offline notebook.
Whether Surf gets to be a template for AI-first research tools will come down to execution—the accuracy, latency, and the way the local-first approach scales. But between the proliferation of answer engines in one market and note apps in another, Deta’s hybrid is a stab at integrating them into a single, editable, reliable workspace.
