I built Wisprs, an AI transcription tool that's honest about accuracy
Every tool I tried promised 99% accuracy, then choked on real audio: co-hosts overlapping, bad mics, noisy cafes.
Wisprs flips it: excellent on clear audio, varies with conditions — and we surface AI summaries, chapters, and action items so you don't have to read walls of text anyway.
100+ languages, speaker labels, export to TXT/SRT/VTT/DOCX.
Free to start, $25/mo when you outgrow it. :)
Genuinely curious what your experience with speech-to-text (STT) tools has been and what you wish the likes of Turboscribe & Otter would address?
Interesting angle.
The thing I'd be careful with is that "honest about accuracy" is a product truth, but not necessarily the reason someone leaves an existing transcription workflow.
The real decision may be earlier than accuracy itself.
I would not make that call casually in a thread because it changes who Wisprs should speak to, what problem it should lead with, and what makes someone switch in the first place.
Curious how you're thinking about that distinction.