Guide

How to Search Inside Multiple PDFs at Once on iPhone, iPad, and Mac

You have forty PDFs and one question: which of them mention the thing you're looking for — and where? Opening each file and pressing Cmd+F does work, once per file, forever. This guide covers what your Mac, iPhone, and iPad can already do without installing anything, where those built-in tools genuinely fall short, and how an import-and-index approach closes the gap — including for scanned documents that ordinary search can't see at all.

The problem: Spotlight and the Files app only get you so far

Searching inside one PDF is a solved problem on every Apple platform. Searching across many runs into three separate walls:

• File-level answers to passage-level questions. The built-in tools can tell you which files contain a word. They are much worse at showing you the passages, in context, ranked, across all files at once.
• Literal matching only. A search for "termination" will not find the contract that says "either party may end this agreement." The OS matches strings, not meaning.
• Scanned PDFs are often invisible. A PDF that's really just photographs of paper has no text layer, so a text search frequently has nothing to match against.

None of this means the native tools are useless. On the Mac in particular, they're better than most people realize — so let's start there.

On a Mac: what Spotlight, Finder, and Preview can do natively

Spotlight: the fastest "which files mention this?"

Press Cmd+Space and type your term. Spotlight indexes the text content of PDFs on your Mac, so documents containing the word appear under the Documents group in the results. Put multi-word phrases in quotes — "force majeure" — to match the exact phrase rather than either word alone.

Finder: content search you can scope and save

Spotlight's window is cramped. Finder runs the same index with more control:

1. Open the folder that holds your PDFs and press Cmd+F.
2. Type your term, and in the suggestions that appear under the search field, choose Content contains (not "Name matches") so it searches inside the files.
3. Click the + button below the search field and add a filter: Kind is PDF.
4. Toggle the scope between the current folder and "This Mac" as needed. Click Save to keep the whole query as a Smart Folder that stays up to date.

Terminal: the same index, scriptable

If you're comfortable in Terminal, mdfind queries the Spotlight index directly and prints file paths you can pipe anywhere:

mdfind -onlyin ~/Documents/Contracts 'kind:pdf "force majeure"'

Where the Mac's native tools break down

All three of these share the same ceiling, because they share the same index. They return a list of files — you still have to open each hit and Cmd+F your way to the passage. They match literal strings, so synonyms, paraphrases, and concepts slip through. And a scanned, image-only PDF usually contributes nothing to the index: macOS has gotten better at reading text in images, but there's no guarantee any given scan was ever OCR'd, and in practice image-only PDFs routinely come back as false negatives. A search that quietly skips some of your documents is worse than one that fails loudly — you don't know what you missed.

On iPhone and iPad: why the native options are thin

The picture on iOS and iPadOS is simpler and worse. The Files app's search field matches file names, dates, and other metadata — it is not a reliable full-text search of what's inside your PDFs. Once you open a single PDF in Files, the built-in viewer does have a working text search, and it's fine for one document at a time. But there is no supported way to type one query and have it checked against the text of fifty PDFs sitting in a folder in Files or iCloud Drive. On a phone, the "open each file, search, close, repeat" loop is even slower than on a Mac.

So on every Apple platform, the honest summary is the same: single-document search is built in; multi-document search needs an index that the OS doesn't give you. That's the job of the next section.

The import-and-index approach: search every PDF at once, by keyword or by meaning

The reliable way to search many PDFs at once is to stop asking the operating system to scan files in place and instead bring the documents into an app that builds a proper index of them — every page, every file, one search box.

This is what OpenIntelligence is built for. It's a free download on the App Store for iPhone, iPad, and Mac. One requirement to know before you tap install: it needs iOS, iPadOS, or macOS 26 or later and Apple Intelligence–capable hardware — an iPhone 15 Pro or later, or an iPad or Mac with an M1 chip or newer.

The workflow:

1. Import your PDFs — from the Files picker, the share sheet, or drag and drop on Mac and iPad. It isn't limited to PDFs, either: Office and iWork documents, spreadsheets, presentations, notes, scans, code, and even audio and video recordings can all go into the same library.
2. Let it index. Every document is indexed locally on your device — a full-text keyword index (SQLite FTS5, the same battle-tested engine used across the industry) plus a semantic index that captures what passages mean, with retrieval accelerated by Metal across the CPU, GPU, and Neural Engine.
3. Search once, across everything. A keyword search finds exact terms — a defined term, a part number, a name — across every imported document at once. A semantic search finds passages about your topic even when the wording differs, which is exactly the query the OS tools can't run: "termination" finds the clause that never uses the word.

Honest scoping: OpenIntelligence searches what you import into its library. It does not sweep your whole filesystem in place, and it is not a Spotlight replacement — Spotlight remains the right tool for "where is that file on my disk?" The library approach is the tradeoff that buys you full-text and meaning-based search of every page: you decide what goes in, and everything in it is genuinely searchable.

Everything above happens on your device: the index lives locally, search works in airplane mode, there's no account to create and no API key to paste, and the App Store privacy label reads "Data Not Collected." If you want the deeper story on what on-device AI can and can't do on Apple hardware, we've written it up honestly in On-Device AI on iPhone, iPad, and Mac: What It Can Actually Do.

Scanned PDFs and photos of paper: making them findable with OCR

Remember the third wall: a scanned PDF is pictures of pages, not text. No text layer, nothing for a keyword index to store, no matches — the document is effectively invisible to search, even though a human can read it perfectly well.

When you import a scan into OpenIntelligence, it runs Apple's Vision OCR on the pages, on-device, and indexes the recognized text alongside everything else. From that point on, your scanned lease is as searchable as a born-digital PDF — by keyword and by meaning — and its pages show up in the same combined results.

One caveat worth stating plainly: this makes scans findable inside the app's library. It does not modify your original file or export a new "searchable PDF" with an embedded text layer. If what you need is a searchable PDF file — say, to email to someone else or file with a court — you'll still want a scanner app that writes the OCR text layer into the PDF itself for that step. And OCR on rough source material — faded thermal paper, handwriting, low-resolution faxes — has real limits everywhere, this app included; for anything that matters, spot-check a page or two against the original.

From finding to asking: turning a search into a cited answer

Once every document is in one indexed library, a second thing becomes possible that no amount of Cmd+F ever will: instead of searching for a word, you can ask a question — "what does the lease say about subletting?" — and get an answer assembled from the relevant passages, with tappable citations that jump to the exact source pages so you can verify every claim yourself.

Just as important is what happens when the answer isn't there: OpenIntelligence abstains. If your documents don't support an answer, it says so rather than inventing one. For a search tool, that property matters more than it sounds — a fabricated answer is worse than an empty results list, for the same reason a silently-skipped scan is worse than a loud failure. The full question-answering workflow, including how it behaves offline, is covered in How to Chat With a PDF Offline.

Tips for big libraries: research papers, contracts, and archives

• Use keyword search for defined terms, semantic search for concepts. In contracts, exact strings matter — search "Material Adverse Effect" as a phrase. In a pile of research papers, the same idea hides behind different vocabulary, which is where meaning-based search earns its keep.
• Import related documents together. A question is answered from the library you've built, so a library that actually contains all twelve leases will out-answer one holding nine of them.
• Spot-check your worst scans after import. Search for a phrase you can see on the scanned page. If OCR read it, everything else on that page is findable too.
• Recordings are documents too. Meeting audio and lecture videos can be transcribed on-device and indexed into the same library, so one search covers your PDFs and what was said out loud — see Transcribe and Summarize Recordings Without the Cloud.
• Keep using the native tools for what they're good at. Spotlight and Finder remain the fastest way to locate a file by name or find which folder something lives in. The indexed library is for the question they can't answer: what's written inside all of these, everywhere, at once.

That's the honest state of multi-PDF search on Apple platforms in 2026: real native options on the Mac with real ceilings, almost nothing native on iPhone and iPad, and an import-and-index approach that turns a folder of unsearchable documents into one library you can search — and question — in a single pass, entirely on your device.