In-App Voice AssistantDevelopment
Let users speak to your app to search, fill forms and run actions, with the assistant tied into your own screens and permissions.
In-App Voice Assistant Development: what the work involves
Typing on a phone is slow, and in many markets users prefer to speak, often switching between Urdu and English in one sentence. Apps that depend on long forms and nested menus lose people halfway, and field staff using gloves or one hand struggle to log data at all. A tap-only interface treats those users as an afterthought.
DevKey builds an assistant that lives inside your application, not a separate bot. Audio is captured on the device, transcribed by a speech model, and interpreted against the actions your app exposes, such as search orders, add an expense or open a customer. The assistant calls those functions through your existing API under the logged-in user's rights, then answers in text and, if wanted, synthesised speech. Unclear commands prompt a short question, and sensitive steps ask for explicit confirmation.
Core features
Push-to-talk and hands-free modes
Users can hold a button or use a wake gesture, with clear listening indicators and a way to cancel mid-way.
Speech recognition for Urdu and English
Models are chosen and tested on your users' accents and code-switching, with custom vocabulary for product and place names.
Action mapping to app functions
Spoken requests are turned into structured calls to your existing endpoints, so the assistant can do what the app can do, and nothing more.
Confirmation for risky actions
Payments, deletions and messages sent to customers require an explicit spoken or tapped confirmation that shows exactly what will happen.
Spoken and visual replies
Answers appear on screen and can be read aloud, so the assistant remains usable in noisy places and silent environments.
Session logging and replay
Transcripts and chosen actions are recorded with consent, helping you find misheard phrases and improve vocabulary.
What we get right before launch
Noise, accents and latency
Markets, vehicles and clinics are loud, and a slow response feels broken. We test on real devices in real environments, use streaming recognition where possible, and design for graceful retries.
Privacy of voice data
Audio can contain personal information. We ask for permission, avoid retaining recordings by default, tell users where audio is processed, and offer on-device recognition for sensitive apps where accuracy allows.
Voice is not always the best input
Some tasks are quicker by tapping. We add voice where it removes friction, such as dictation or search, and keep the normal interface intact instead of forcing every flow through speech.
Tools and technology
- OpenAI Whisper and Realtime API
- Google Speech-to-Text
- Anthropic Claude
- Flutter
- React Native
- Node.js
- FastAPI
- WebRTC
- Docker
Common questions, answered
Will it understand Urdu and Pakistani English accents?
Reasonably, but accuracy varies by engine, accent and noise. We benchmark candidate speech models on recordings from your actual users before choosing, and add custom vocabulary where names and terms are misheard.
Can it work offline?
Limited on-device recognition can work offline, with smaller models and lower accuracy. Understanding the request and calling your backend normally needs a connection, so we design a graceful fallback.
Can the assistant take actions on behalf of the user?
Yes, within the permissions of the logged-in account and only for actions you expose. Anything consequential asks for confirmation, and every action is logged.
Does it need a native app?
No. Browser-based assistants work on web apps through microphone permissions, though native apps offer better audio control and background behaviour. We recommend based on your existing product.
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Ready to start your In-App Voice Assistant Development project?
Tell us what you need and we will come back with a clear scope, timeline and the questions worth answering before any build starts.