s3-lambda VS The FastScribe
Compare s3-lambda VS The FastScribe and see what are their differences
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FastScribe turns audio and video into timestamped text. Drop a file, get a transcript with TXT, SRT and VTT export.
Two things make it different. Your first file needs no account at all, not an email, not a card. And your audio never reaches a third-party AI service: transcription runs on a machine I own and operate, and the file is deleted the moment your transcript is ready.
Free: first file with no signup, then 5 a day with an account. Pro is $12/month for files up to 2 GB and 5 hours, batch uploads and DOCX export.
I built this because every transcription tool I tried wanted an account before it would tell me whether it was any good, and most of them are a web form in front of somebody else's speech API. Your recording gets handled by two companies and you agree to both retention policies.
So, FastScribe runs on a local server. There is a GPU in it. Your file is uploaded, transcribed on that machine with no outbound network call, and the audio is deleted the moment the text exists. No third-party AI or cloud service ever receives it.
s3-lambda The FastScribeThe FastScribe's answer:
Two things. Your first transcription needs no account at all: no email, no card, no trial. And transcription runs on hardware we own and operate rather than a third-party speech API, so your audio never reaches OpenAI, Google or AWS, and it is deleted the moment your transcript is ready. Most transcription products are a web form in front of somebody else's speech service, which means two companies handle your recording and two retention policies apply.
The FastScribe's answer:
Because you can judge it on your own audio before giving us anything. The first file is free with no signup, so accuracy claims are not the selling point: you test it on your own recording in two minutes. Beyond that, the free tier is real rather than a demo (5 files a day with an account), every export format is on every tier including SRT and VTT, and the privacy position is architectural rather than a policy promise. If your recording is genuinely poor, our own guides tell you how to fix or that no automated tool will fix it. We would rather say so than waste your afternoon.
The FastScribe's answer:
People who have a recording and need it as text, without a subscription or a procurement conversation. Journalists and researchers transcribing interviews, podcasters producing show notes and captions, students working through recorded lectures, and professionals handling confidential dictation where sending audio to a third-party AI service is not acceptable. Also anyone who tried running Whisper locally and found it too slow on their laptop.
The FastScribe's answer:
It started as arithmetic. Building on a cloud speech API means paying per minute, which makes every free file a direct cost, which is why most free tiers in this category are tiny or gated behind an account. I already ran a server, so I put a GPU in it instead. The marginal cost of one more transcription became electricity, which is what makes a real free tier possible. The privacy position was accidental: because there is no third-party API in the path, no outside service ever receives your audio, and it can be deleted the moment the text exists. I backed into the best thing about the product by being cost-conscious.
The FastScribe's answer:
Next.js and TypeScript on Vercel for the web application, Supabase (PostgreSQL with row-level security) for data and authentication, Cloudflare R2 for upload transcription storage (for Pro members), and Stripe for payments. Transcription runs on self-hosted hardware: specialized, reinforced whisper.cpp with CUDA on an NVIDIA GPU, with Silero VAD and ffmpeg in the pipeline. Python workers pull from a queue on that machine.
The FastScribe's answer: