How to search across Notion, Google Docs, and YouTube at once

Short answer: you connect each tool to a single search layer that reads the full content. Notion docs become searchable text. Google Docs become searchable text. YouTube videos become searchable transcripts. Then you type a plain-English question into one bar and get back the doc, the section of the doc, or the moment in the video where the answer lives.

None of these tools talk to each other natively. If your team’s knowledge is spread across all three, the only way to actually search across them is to plug them into something that does.

Why it’s a pain today

Notion has search inside Notion. It’s decent for finding pages by title or pulling the doc you wrote last Tuesday. It does not see your Google Docs, and it does not transcribe your YouTube videos.

Google Drive has search inside Google. It pulls Docs, Sheets, Slides. It does not see your Notion. It does not transcribe your YouTube videos either.

YouTube has search inside YouTube. It searches video titles, descriptions, and (recently) captions where they exist. It does not see your Notion. It does not see your Drive.

Everything you’ve made lives in three separate silos with three separate search bars. When someone on your team needs an answer, they have to remember which silo it’s in and switch between three apps to find it.

What “search across all three at once” actually means

A few things need to happen.

Every Notion page gets indexed as text. Your nested databases, your meeting notes, your wiki pages.

Every Google Doc you give access to gets indexed as text. Either through an OAuth picker where you choose which folders or files, or through a service-account export for company-wide rollouts.

Every YouTube video gets transcribed. Auto-captions are a starting point. Full transcription with timestamps is what you actually want, because then results can deep-link to the moment.

All three then sit in one searchable workspace. You type a question. The result tells you whether the answer lives in a Notion page, a Google Doc, or 23 minutes into a YouTube video, and links you straight there.

How to set it up

Three options.

One: build it yourself. Notion API for the docs, Drive API plus OAuth for Google, yt-dlp plus Whisper for YouTube transcription. Vector storage for embeddings. Roughly the same engineering lift as building a knowledge base from scratch.

Two: pile multi-search tools together. Glean, Slite, and similar tools index across SaaS sources. Most are priced for company-wide deployments, not the operator who’s running a course and an agency on the side.

Three: use a dedicated knowledge layer that has integrations for all three. Findery has Google Docs (real, with OAuth and Picker), YouTube (channel URL paste, transcription on our own GPUs), and Loom (paste URLs, then transcription). Notion itself is on the list and ships next. For now, teams paste the docs they want indexed into Findery as Markdown or PDF. Setup takes about a minute on a free trial.

What it looks like once it works

Your team stops mentally cataloguing which tool the answer is in. They search Findery, they find the thing, they get back to work.

Onboarding speeds up because new hires can ask the same questions that returning staff used to. The answer is one query away regardless of where it’s stored.

Documentation discipline gets easier. The cost of “where did we put that doc” drops to almost nothing, so you can let the docs live where they make sense (Notion for collaborative editing, Drive for client-facing exports, YouTube for training videos) without worrying that any of it becomes invisible later.

A note on Notion AI and Google’s NotebookLM

Notion AI answers questions inside Notion. NotebookLM answers questions from sources you upload to NotebookLM. Neither searches across all your tools at once. They’re both pointed at one silo each.

The thing that’s missing is the cross-source layer. That’s what Findery is.