Discovery
We map your audio use case, existing stack, and success metrics, then agree on model, voice, language, and latency requirements.
SpeechifyAI engineers embed with your team to integrate, evaluate, and ship production speech against the systems and constraints you already have.
Production audio needs voice selection, streaming playback, pronunciation control, and load testing against real content. Your forward-deployed engineer owns that delivery gap with your team, in your stack.
The engagement stays accountable to production outcomes, not a handoff document or a proof of concept.
We map your audio use case, existing stack, and success metrics, then agree on model, voice, language, and latency requirements.
Our engineers work with your team on speech API integration, voice mapping, streaming playback, and delivery quality using your real text.
Validate audio quality, load, and failure handling before rollout, with clear ownership of the production integration.
As usage grows, review real synthesis results, tune pronunciation and delivery, and extend regression tests so quality holds.
Your engineer works across the synthesis path, from model and voice selection to playback and production validation.
Evaluate Simba models and compatible voices against your content, language coverage, and listening criteria.
REST, Python, or TypeScript integration with your application and audio delivery path.
Map existing voices and tune pronunciation, SSML, and pacing against representative content.
Integrate chunked audio, buffering, and output formats appropriate for your browser, application, or phone system.
Listening checks, latency measurements, and load tests that reflect your real synthesis workload.
Document integration ownership, consent requirements for cloned voices, and operational checks with your team.
Built for complex delivery
Bring the use case. We will scope the integration, listening criteria, and rollout with your team.
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