01
Technical domains
Medicine and other specialist fields use words and phrases you rarely hear anywhere else.
Solutions · Transcription
Transcription That
Knows Your Words.
Base models break on technical vocabulary and local dialects. Parsec deploys models post-trained on your audio, down to the individual client.
The need to specialize
Better in general. Still rough at the edges.
Transcription has improved by leaps and bounds. For a specific use case it still breaks in two ways, and that is not going to change.
02
Languages and dialects
Coverage lags beyond the biggest languages, and even those miss as soon as a local dialect enters the mix.
03
Cost and latency
An hour-long meeting is ~5,000 words, and voice needs answers in milliseconds. Models stay small and lose quality at the edge.
Specialized at scale
A model per client, not per company.
Point your production traffic at Parsec and get custom intelligence back, without training, maintaining or serving your own models.
The way people speak is unique to them, their region and their role. We deploy models that reflect it, so every client can see their transcription improving.
The simple truth
Parsec vs transcription APIs vs self fine-tuning.
| Parsec | Transcription APIs | Self fine-tune | |
|---|---|---|---|
| Method | Post-trained on your audio | One size fits all | Fine-tune |
| Domain terms and dialects | Learned from your traffic | Keyword lists | As good as your labels |
| Evals | Inferred from production traffic | Public WER benchmarks | Set up yourself |
| Serving | Optimized streaming cluster | Their API | Stand up yourself |
| Detail | Client level | One size fits all | Firm level |
| Cost | Your existing transcription line item | Per minute | Always-on GPUs |
| First-time effort | One-line switch | Zero | Hand labeling plus ML engineer hours |
Cut Cost. Raise Accuracy.
Especially in the languages and domains that off-the-shelf models get wrong.