mattInqScribe is pleased to sponsor the 2026 WCQR – World Conference on Qualitative Research. We originally built InqScribe to help with our own qualitative research projects, so the needs and workflows of researchers are baked into our design.
The core idea is simple: a text-first editor with a built-in media player. As you type free-form notes, you can drop time codes exactly where insight happens. Those time codes stay clickable, so you can jump straight back to moments you want to revisit, share in lab meetings, or present in a talk.
Most actions live on the keyboard so you’re not chasing your mouse across windows. Tap a hotkey to skip back a few seconds, slow playback when precision matters, and keep your hands in the flow while you capture what’s unfolding. If you prefer to use a USB foot pedal, that works too. Customizable snippets and search-and-replace help you tune transcripts without breaking rhythm.
Coding is intentionally organic. Insert your own codes in-line as you notice patterns. Unlike many qualitative analysis tools, InqScribe does not impose a rigid taxonomy or brittle line-by-line user interface on you. Whether you’re creating word-for-word transcriptions or rich qualitative descriptions of visual or auditory cues, InqScribe provides the flexibility to match your work style.
And when you need captions, you can export your transcript into a number of industry-standard caption formats for easy subtitling.
Most importantly, InqScribe is simple to use. Simply drag your media file into the InqScribe window, press the tab key to start your video, and start typing your observations. It’s that simple. And yet, InqScribe is incredibly powerful and highly customizable. Create your own libraries of frequently used phrases or codes, map hotkeys to any media control, or adjust time code offsets to match your transcript to on-screen timestamps.
And some big news: Coming in January, InqScribe will support on-device privacy-first Al transcription. No subscriptions, no usage limits, and no delays. Your data remains on your computer (no cloud uploads) and is never used to train Al models. We understand how critical this is for maintaining the privacy of research subjects and IRB compliance. If you want early access, you can sign up for the public beta at https://www.inqscribe.com.
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