Bulk Tag HEIC Photos, WebP, and RAW at Scale in 2026

Your shared folder has 22,000 photos in it. Roughly half are HEIC straight off the team's iPhones, a few thousand are WebP that someone exported for the website, there is a folder of camera RAW from the last shoot, and the rest are ordinary JPEG. You try one tagging tool and it silently skips every HEIC. You try another and it demands you convert everything to JPEG first. Tagging mixed photo formats at scale is where most tools quietly fall over.

Quick answer: To bulk tag HEIC photos, WebP, and RAW at scale, use a tool that decodes each format on ingest rather than one that writes keywords back into the file. Decode-on-ingest tools read the picture, send it to a vision model, and store tags in a separate searchable catalog, so HEIC, WebP, AVIF, and RAW all tag in place with no conversion step and no change to your originals. EXIF and IPTC writers, by contrast, often cannot read HEIC or RAW at all and force a slow batch conversion first.

Why HEIC, WebP, and RAW break most tagging tools

The formats themselves are the problem, and each one breaks tools in a different way.

HEIC is the default camera format on iPhones since 2017, and it is everywhere a team uses phones. It is a container built on HEVC (H.265) compression, which is patent-encumbered. Plenty of software never licensed an HEVC decoder, so it skips or errors on HEIC files instead of reading them. Apple's own HEIF and HEVC support notes spell out how narrow native support still is. Web browsers other than Safari cannot even render HEIC, which is why so many tools punt on it.

RAW is not one format. It is hundreds of camera-specific variants: Canon CR3, Nikon NEF, Sony ARW, Fujifilm RAF, Adobe DNG, and more. Each needs its own decoder, so a tool that claims "RAW support" often means a handful of popular cameras and a shrug at the rest.

WebP and AVIF are the web-native formats. A marketing team exports them for fast-loading pages, as Google's web.dev image format guide recommends, then a year later cannot tell which hero-final-2.webp is which. Older taggers built only for JPEG ignore them.

Note. "Supports HEIC" can mean two very different things. Some tools can read HEIC to generate tags. Others can only write tags into a HEIC file, which is the harder problem and the one most fail at. For a searchable catalog you only need the first.

The two ways to tag a file, and why one survives format chaos

Two different approaches to tagging explain why format support varies so wildly.

The metadata writer embeds keywords directly into the image file's EXIF or IPTC fields. To do that it has to read and write every format you give it. That is fine for JPEG, a decades-old standard. It falls apart on HEIC and RAW, where writing metadata safely is genuinely hard and many tools refuse to try. This is the world of desktop keyword apps and EXIF injectors, and it is why iPhone HEIC libraries cause so much grief.

The decode-on-ingest approach reads each file, decodes it to raw pixels in memory, sends those pixels to a vision model, and writes the tags to a separate searchable database. The original file is never touched. Once a file is decoded to pixels, the model neither knows nor cares whether it started as HEIC, WebP, AVIF, RAW, or JPEG. Format support becomes a decoding problem solved once, server-side, instead of a writing problem re-solved for every format.

Tagrly is built the decode-on-ingest way. It reads HEIC, WebP, AVIF, and common RAW straight from Google Drive or Dropbox, decodes each one, and tags it in place. Your originals keep their exact bytes and stay where they are, which is the same in-place model covered in the Google Drive bulk-tagging guide. Foto Owl and a few other cloud catalogs work on a similar in-place principle, so Tagrly is one option in this category rather than the only one.

The free and cheap ways to handle mixed formats

Before reaching for a paid tool, here is the honest survey of what you can do for free or cheap.

Convert everything to JPEG first (free, but costly)

The brute-force free option is to batch-convert your HEIC and RAW to JPEG, then tag the JPEGs with whatever tool you already have. macOS Preview, the free ExifTool command-line utility, and dozens of online converters do this. It works, but it doubles your storage, breaks the link between tags and your true originals, and throws away RAW's editing latitude. Fine for a small one-off batch. For a 20,000-photo library that keeps growing, the conversion step becomes a permanent tax.

Lightroom or Bridge for RAW (cheap, single-machine)

If your library is RAW and you already pay for Adobe, Lightroom Classic reads almost every RAW variant and lets you keyword. The catch applies to every desktop tool: it runs on one machine, the tags live in a local catalog, and a team cannot share the result. This is a solo-photographer answer, not a team answer.

Single-format AI taggers (cheap, but format-limited)

Some inexpensive AI keyword services handle JPEG and a couple of other formats well but quietly skip HEIC or only export keywords you then have to inject yourself. Several popular cloud taggers have no native HEIC writing, so iPhone photos need an extra ExifTool round trip. If most of your library is phone photos, check format support on the vendor's own page before you commit, because this is exactly where the cheap tools cut corners.

Tip. Whatever tool you are evaluating, hand it five HEIC files and three RAW files from your actual cameras and watch what happens. If it skips them, errors, or asks you to convert first, you have your answer in two minutes instead of two weeks.

What good tagging output looks like, regardless of format

The point of tagging mixed formats is that the output should be identical no matter what the file started as. A focal-subject tag for an iPhone HEIC and a focal-subject tag for a camera RAW of the same scene should read the same, because the model sees the same pixels.

This is where the focal-subject tagging method from the complete guide to bulk AI photo tagging does its work. The model identifies the single dominant subject of the photo first, then the supporting context, and ranks the focal subject above the context in search. A query for "rooftop sunset" surfaces the HEIC phone shot, the WebP web export, and the RAW from the shoot side by side, ranked by how central that subject is, not by which format each happens to be.

For internal search, the Standard tier produces short structured tags like "rooftop, sunset, skyline, cocktails." For anything headed to a public page, the Premium tier writes editorial-grade alt text, a full sentence you can paste straight onto a site. The format is irrelevant to both. You can see the same photos run through both tiers on the output quality comparison page.

Tip. If you want to see decode-on-ingest tagging on your own mixed-format folder, test it on a sample folder. Tagrly's free tier tags the first 100 photos in any Drive or Dropbox folder, no credit card, so you can drop in a folder of HEIC, WebP, and RAW and watch them tag as one library.

Speed and cost when formats are mixed

Does decoding HEIC and RAW slow the scan down? A little, but not enough to change the plan. RAW files are large, often 20 to 50 MB each, so they take longer per photo than a 2 MB JPEG, while HEIC, WebP, and AVIF decode quickly. Across a mixed library it averages out, and it stays a thin slice of the total because the vision pass dominates the clock. The full breakdown is in how fast AI photo tagging is on a 100,000-photo library.

As a real reference point, a working production library of about 19,000 wedding and event photos mixed camera JPEG, edited exports, and phone shots in one archive. It tagged as a single searchable catalog in roughly 9 hours on a conservative overnight run, not one job per format, with no pre-sorting or conversion. On cost, you are billed per photo tagged, not per format, so a HEIC costs the same as a JPEG. The only money format costs you is the conversion tax you avoid by not converting at all.

How to pick a tool for mixed-format libraries

Match the tool to where your photos live and who needs to find them.

• Pick a decode-on-ingest cloud catalog (Tagrly, Foto Owl) if your photos are in Google Drive or Dropbox, your library mixes HEIC, WebP, and RAW, and a team needs to search it. You tag in place with no conversion and no per-format jobs.
• Pick Lightroom Classic or ON1 if you are a solo photographer, your library is mostly RAW, and you live in a desktop editor already. They read RAW well; they just do not share across a team or read HEIC keyword-writing cleanly.
• Pick a desktop EXIF or IPTC writer if you specifically need the keywords embedded inside the files themselves and your formats are JPEG-heavy. Confirm HEIC and RAW writing before you buy, because that is where these tools most often fail.
• Pick free conversion plus a basic tagger if this is a small one-off batch and you do not mind converting. For a growing library, the conversion tax makes this the wrong long-term answer.

The honest takeaway: format support separates tools that work on real 2026 libraries from tools that only work on a tidy folder of JPEGs. iPhone HEIC, web WebP, and camera RAW are the normal contents of a working library now. A decode-on-ingest tool treats them as one searchable thing; a metadata writer treats every format as a fresh problem. For most teams with mixed formats in cloud storage, decode-on-ingest is the answer, and the fastest way to confirm it fits is to point it at a real folder of your own photos and watch the HEIC and RAW tag without a fight.