Best fit

Strong fit

  • Scripted read-aloud, assessment, and pronunciation practice
  • Workflows with known prompts, transcripts, or reference text
  • Teams that want lower-friction APIs and structured outputs

Weak fit

  • Open-ended conversation scoring without reference text
  • Generic speech-to-text replacement
  • Broad voice-agent platforms where assessment is not central

Integration path

1

Evaluate

Use the playground with your own prompts and sample audio.

2

Prototype

Start with POST /v1/scores or @prosody/sdk.

3

Decide

Measure output quality, response shape, latency, and fit with your product logic.

Suggested evaluation checklist

Question What to look for
Does your workflow have reference text? Prosody is strongest when the expected utterance is known.
Do you need word and phoneme detail? Check whether your UI or QA workflow benefits from structured timing and per-word signals.
Do you need batch, live, or both? Batch is the public default today. Streaming is selective beta after batch fit is proven.
Do you need a generic speech vendor? If you mainly need transcription, Prosody is probably the wrong first layer.
Can one good prompt prove the workflow? Start with a narrow read-aloud or known-transcript task before testing broader product scope.

Fastest useful evaluation packet

These three things are enough to tell whether Prosody is worth integrating. You can send them over or just try the playground with your own prompts first.

1

Known prompts

Send 3-5 reference utterances that actually matter to your workflow.

2

Representative audio

Include a few recordings that show strong, weak, and edge-case pronunciations.

3

Decision lens

Tell us whether you are testing output quality, UI fit, latency, or pricing first.

What partners usually check first

Reference-guided API
<30ms pipeline target
20.7ms GPU alignment
$0.004/min pricing
4,100+ tests
Playground live

The shortest path is usually: try the playgroundread the docscheck pricingask us anything.