What I like most about remio is that it doesn’t feel like just another AI chat window. It helps turn scattered information from my daily work into context that I can actually use again.

I deal with many different kinds of information every day: meeting recordings, PDFs, local documents, web articles, WeChat articles, emails, development discussions, latest technical articles, competitor research, and random thoughts. Before remio, these things were spread across browser bookmarks, Obsidian, local folders, chat history, AI conversations, and temporary documents. The problem was not that I didn’t save things. The problem was that when I actually needed them, I still had to search, reread, and reorganize everything manually.

remio gives these materials a place where they can accumulate over time, be searched, questioned, analyzed, and used for real work. I use it for meeting analysis, saving web articles and PDFs, writing reports and articles, preparing talks, organizing technical context, and recently, for longer agent tasks and deep research.

The agent part has become especially useful for me. I don’t just ask simple knowledge-base questions anymore. I can ask remio to research a topic, compare different sources, organize the structure, and produce a report or clear analysis. Because it can work with both external information and my own files, the result feels closer to my real working context.

Compared with Obsidian, remio requires much less manual organization. Obsidian is great for writing and Markdown-based notes, but I don’t always have time to polish every saved item into a clean note. With remio, I can put materials in first and make them searchable, summarizable, and reusable later.

Compared with NotebookLM, remio feels more continuous. NotebookLM is good for asking questions around a selected set of sources, but remio feels more like a long-term work environment. My materials come from web pages, local files, recordings, emails, chat history, PDFs, and many other sources, and they keep growing over time.

I’ve also tried a few general agent tools. For my own workflow, remio has been especially helpful for document-heavy and research-heavy tasks because it already sits on top of my own knowledge base and historical materials. I don’t need to explain the background again and again. The cost also feels more predictable and easier to control in longer tasks.

It still has room to improve. Because remio does many things, new users may need some time to understand where to start. I also hope the team keeps improving context management, especially making long tasks more efficient and reducing unnecessary token usage.

Also, thanks to the remio team. I can feel the product is being actively improved, and I hope they keep shipping practical features instead of just chasing AI buzzwords.

That said, remio already feels very close to a work assistant that really understands me. It remembers my materials, connects them when needed, and helps me move from scattered information to actual output.

For me, it has become more than a knowledge base. It is becoming the context entry point for my daily work.