Convert speech into accurate text in real time — and know who said it.
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Built for Indian conversations, engineered for production latency.
Our own speaker-segmentation model, post-trained on Indian conversational audio: rapid turn-taking, crosstalk, phone-line quality and Hindi–English code-switching. Off-the-shelf diarizers are trained on Western meeting speech and fall apart here.
~1.5% of audio time · a 2-min call is diarized in under 2 sHindi comes out in Devanagari, English in Latin, in a single decoding pass. No transliteration stage, no post-hoc script guessing, no romanized soup.
“मैं कल office जाऊँगा” — the way India actually writesOur post-training on Indian conversational speech removes the failure modes that break call analytics: repetition loops, fabricated openers, destroyed digit runs, lost names and amounts.
Numbers, names and amounts survive the transcriptHalf-precision weights with fused attention kernels, shape-bucketed padding with pre-warmed kernels so the first request is as fast as the thousandth, and beam search that stops the moment it is confident.
Zero cold-start · ~200 clips per minute per GPULive and microphone requests pre-empt batch jobs on the same GPU, so a 60-minute upload never delays a 5-second utterance. Long files flow through an async job queue that is immune to gateway timeouts.
Live requests always get the GPU nextA Conformer engine for 22 scheduled languages and the Hinglish Pro model sit behind the same diarizer and the same API, served from a single GPU. Pick the language; everything else stays identical.
One integration · every Indian language you sell in