Start with the job, not the vendor
Use Whisper, Speechmatics or Azure. FlexSR does not replace them, it sits above them and checks what they produced.
To trust the transcript you already have
Phrases caught on a device with no network
No other system on this page verifies against thesounds that were actually spoken. That is the gapFlexSR was built for.
Now you are in our category. Compare us against Picovoice, Sensory and Vosk in the second table below.
A full transcript
of open speech
Systems we work with
Cloud and open transcription engines. These do a job FlexSR does not attempt. The comparison below is aboutwhere each one runs and what it can and cannot confirm, not about who transcribes better.
Capability | FlexSR | Whisper | Google STT | AWS Transcribe | Azure | Speechmatics | Deepgram |
|---|---|---|---|---|---|---|---|
Runs on edge / low power | Yes, on a Pi | Heavy on Pi | Cloud | Cloud | Containers | On-prem server | On-prem server |
Compute footprint | Low, GPU optional | GPU for real time | High | High | High | High | High |
Add jargon without retraining | Lexicon edit | Prompt or retrain | Model adaptation | Custom vocab | Custom speech | Custom dictionary | Keyterms |
Verifies actual speech sounds | Yes | No | No | No | No | No | No |
Works as a verification layer | Designed for it | No | No | No | No | No | No |
Open-vocabulary transcription | Not supported | Full | Full | Full | Full | Full | Full |
Systems we compete with
On-device engines doing the same job on the same hardware. This is the comparison that decides a purchase, and the one most buyers never get shown.
Capability | FlexSR | Picovoice | Sensory | Vosk |
|---|---|---|---|---|
Runs on-device | Yes, Pi | Yes, to MCU | Yes, DSP | Yes, Pi |
Fully offline / air-gapped | Yes | Yes | Yes | Yes |
Keyword and phrase spotting | Purpose-built | Porcupine, Rhino | Yes | Grammar-based |
Wake-word detection | Via phrase spotting | Category leader | Long incumbent | Not supported |
Verifies actual speech sounds | Yes, the core of it | Phonetic search | Acoustic | No |
Verification layer over other ASR | Designed for it | No | No | No |
Published FRR at fixed FAR | Publishing Q1 2027 | 97.1% at 1 FA / 10h | Vendor benchmark | Higher WER |
What FlexSR does not do
-
No open-vocabulary transcription
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No punctuation, diarisation or summaries
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No semantic understanding of what was meant
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Languages arrive by lexicon, not out of the box
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Early maturity, TRL 6, first pilot running.
Why we do not quote a word error rate
Word error rate measures how well a system guesses a whole sentence it has never heard. FlexSR is asked a narrower question: was this phrase said or not.
The right measures are a false reject rate against a fixed false accept rate, taken on a defined task with a stated sample size. We publish those instead, because a WER figure from us would not mean anything to compare against.