Built for your industry
META-1 extracts compositional action tokens — INTENT_ EMOTION_ ENTITY_ AGE_ GENDER_ alongside transcription. Each domain defines its own vocabulary. Contact centers use INTENT_ALREADY_PAID, psychotherapy uses INTENT_SIMPLE_REFLECTION, avatars use BEHAVIOR_CONFRONT, ROLE_INTERVIEWER.
Contact Centers & Collections
INTENT_ALREADY_PAIDINTENT_PROMISE_TO_PAYINTENT_HARDSHIPROLE_AGENTROLE_CUSTOMERThe Problem
Traditional contact center AI works after the call. Agents get no real-time help. In collections, code-mixed conversations (Hindi-English) break most ASR systems, and intent classification happens too late to guide the call.
How Whissle Solves It
Whissle provides Instant Intelligence during the call. Intent is detected as the caller speaks. In collections, the system classifies caller disposition in real-time — promise-to-pay, disputes, hardship — and triggers the right next action. Code-mixed ASR delivers 20.5% WER on Hindi-English vs 34.7% from cloud providers, at 3x lower latency.
Key Capabilities
| Feature | Details |
|---|---|
| Real-time intent | Detected during speech — already-paid, will-pay, disputes, hardship, refusal |
| Emotion-aware routing | Angry callers auto-escalated; positive sentiment triggers upsell |
| Code-mixed ASR | Hindi-English, Spanglish — 20.5% WER, 150ms median latency |
| AI voice agents | Fully automated agents that resolve calls in 30 seconds with human-quality TTS |
| Per-turn analytics | Each utterance tagged with emotion, intent, key phrases, and compliance labels |
| Conversation summary | Auto-generated summary with clear next actions, ready when the call ends |
Deploy for your use case
Same gateway, any industry. One Docker command.