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Research a Topic Across Your Sources - ONA.UNO Docs

Find and synthesize scattered knowledge across files, clips, mail, and notes

The scenario

You’re preparing for a budget meeting and you know the information you need is scattered: a PDF spreadsheet in your project folder, a web article you clipped last month about market trends, two email threads with cost estimates from your team, and some planning notes in Obsidian. Pulling all of that together manually means opening five different apps and trying to hold the connections in your head.

Here’s how to do it in ONA.UNO in a few minutes.

Switch to Semantic scope and describe what you’re looking for in plain language — a full sentence works better than keywords here. Something like: “What did we learn about Q2 budget planning and trade-offs?”

Semantic search finds items by meaning, not just exact words. So even if your email thread says “cost projections” and your notes say “budget forecast,” both will surface.

Scan the results

The timeline now shows only matching items. Scan through them by reading the AI-generated summaries — this is much faster than opening each document. When something looks important, switch to the Original pane to see the actual source material.

At this point you’re triaging: which items are actually relevant, which are only tangentially related?

Pivot through tags

As you scan results, you’ll notice AI-generated tags. Click a tag that looks relevant — maybe cost-analysis or Q2-planning — to see a tag-level summary and discover related items that your search phrasing might have missed. Tags are a powerful way to expand your scope sideways: they reveal connections between items that you might not have thought to search for.

Synthesize with chat

Now that you have a good filtered set, open Chat. Because your search is committed, chat automatically works with the filtered results — not your entire library. Ask synthesis questions:

  • “What are the main options and trade-offs discussed across these items?”
  • “How did the budget estimates change over time?”
  • “Which assumptions haven’t been validated yet?”

Chat reads across all the filtered items and gives you a single coherent answer with citations back to each source.

Dig deeper with follow-ups

When chat surfaces something interesting, click the citation to jump to the source item and read the original. Then come back and ask narrower follow-up questions based on what you found. This back-and-forth between chat and original sources is where the real value is — chat gives you the overview, and you verify the details.

Export what you found

When you have a usable synthesis, export it. Copy the chat transcript as Markdown with citations, or drag the most relevant items out of the timeline. Everything is portable — you can paste it into your meeting notes, share it with colleagues, or save it for next time.

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