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Get the reportSpeech-to-text Built for How India Speaks
Accurate transcription across Indian languages, code-mixed speech, and real-world telephony audio. Structured output your systems can depend on, live or after the fact.
Speech-to-text That Works The Way Conversations Do
Convin STT is built for how people actually speak not scripted audio or ideal conditions. It handles interruptions, accents, background noise, and natural pauses while producing output systems can depend on.
Built for Indian audio conditions
Trained on live telephony data from Indian contact centers, not studio recordings. Handles noise, accents, and poor connections reliably.
India speaks in many languages. So does Convin'
Code-mixed, multilingual, and regional speech is handled natively without manual language tagging per call.
One API for every stage.
Use the same API for streaming live conversations or processing recorded audio. No separate pipelines to maintain.
Output your systems can depend on
Schema-stable transcripts that don't change structure between calls, languages, or audio conditions.
Built for Indian languages
Conversations in India are often multilingual. Convin STT is built to handle Indian languages and natural switching with English in the same conversation.
Supported Indian Languages
हिन्दी English తెలుగు தமிழ் മലയാളം मराठी ಕನ್ನಡ
Live Telephony Training
Trained on live telephony data from Indian contact centers, not studio recordings
Multilingual Conversations
Handles natural Hinglish, Tanglish, and regional code-switching, not just monolingual audio
Auto Language Detection
Automatic language detection, no need to declare the language upfront per call
Why Indian language Support Is Different Here:
Trained on live telephony data from Indian contact centers, not studio recordings
Handles natural Hinglish, Tanglish, and regional code-switching, not just monolingual audio
Automatic language detection, no need to declare the language upfront per call
Try STT
Turn Conversations Into Reliable, Structured Transcripts
High-accuracy transcription across real conversational audio
Real-time streaming and batch processing
Speaker separation with diarization-ready output
Optional utterance-level time alignment
Language selection and control
Schema-stable output for analytics, QA, and automation
Designed to be predictable, readable, and usable
Applied Across Live Conversations And Post-call Workflows
Post-call Processing (Batch)
Support voice bots and conversational systems that need to understand users as they speak, with low-latency streaming transcription.
Common Scenarios
Contact center call recordings
Sales and support audits
QA and coaching workflows
Compliance and regulatory archives
Why It Works
Cost-efficient processing at scale
Consistent transcript structure
Easy ingestion into downstream systems
Real-time Voice Bots
Support voice bots and conversational systems that need to understand users as they speak, with low-latency streaming transcription.
Common Scenarios
Voice bots and virtual agents
IVR systems with live understanding
Conversational automation
Real-time routing and intent handling
Why It Works
Low-latency transcription
Handles interruptions and natural pauses
Clean speaker turns for live processing
Same Audio. Four Ways to Use It.
Conversations in India are often multilingual. Convin STT is built to handle Indian languages and natural switching with English in the same conversation.
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