Our Focus
CONTEXTUAL SPEECH MODELS
We build foundational speech models that can use long context and memory to understand customer intent instantly.
VOICE IN, TOOL ACTION OUT
Voice is our richest input. Live CRM execution and instant database actions are our richest output.
CARRIER TO INTELLIGENCE
We build low-latency SIP/WebRTC carrier bridges directly into neural inference models for crystal clear audio.
PROACTIVE AND ZERO DEAD AIR
Great voice agents respond with natural pacing, zero awkward pauses, and instant sub-18ms interruption yielding.
Introducing Answrable
Voice AI Research Lab
Answrable AI Research introduces the new Advanced Voice Lab. Learn how we're solving real-time voice latency, streaming direct audio tokens, and orchestrating mid-call database actions...
“The goal isn't just for Voice AI to talk back to callers. It's to understand intent, eliminate latency, and execute business actions mid-call without missing a beat.”
From the Lab
HCM-1: A neural voice model built for real-world telephony
Today, Answrable Research Lab is introducing HCM-1, our proprietary foundation voice model for real-time full-duplex conversations on raw carrier audio...
Why supporting 40+ regional dialects and Hinglish is hard
At Answrable, we're building toward true bilingual fluency: natural, accurate speech recognition across India's Tier 1-3 markets without phonetic drift...
Technical challenges behind building sub-160ms voice agents
Answrable is built on solving tough carrier telephony challenges — from streaming raw audio tokenization to mid-call asynchronous database tool execution...
Eliminating dead air in conversational speech turn-taking
Explore real-world acoustic benchmarks, why cascaded bot wrappers (STT + LLM + TTS) struggle with awkward delays, and how Answrable eliminates dead air...
Advancing autonomous human-voice customer interfaces
Answrable is rethinking enterprise conversational interfaces — reducing telephony friction and eliminating latency so automated calls feel effortless...
Answrable HCM-1 vs Industry Models & Stacks
Detailed engineering comparison of Answrable's direct audio foundation architecture against OpenAI Realtime, cascaded bot wrappers (Retell/Vapi), Bland AI, and legacy IVR infrastructure.
| Architectural Metric | Answrable HCM-1 8B Direct Audio Engine | OpenAI RealtimeGPT-4o Audio API | Retell AI / VapiCascaded (STT+LLM+TTS) | Bland AI / Legacy IVRBot Wrappers & DTMF |
|---|---|---|---|---|
| Core Acoustic Architecture | Continuous Wave Tokens (Direct Audio-to-Audio) | Multimodal Token Streaming | Cascaded (Deepgram → LLM → ElevenLabs) | Text-wrapper pipeline / Rule-based trees |
| Full-Duplex Turn Latency | 142ms (Sub-180ms Carrier) | 320ms – 480ms | 650ms – 1,100ms | 950ms – 2,200ms |
| Barge-in / Interruption Response | <18ms Instant Yield (Zero Stutter) | ~120ms (Audio buffer flush) | 450ms – 800ms lag | Frequent audio overlap / None in IVR |
| Indian Dialects & Hinglish | 40+ Native Dialects Trained (Zero Phonetic Drift) | English-dominant (Translation & accent drift) | English-centric (Requires external translation) | High WER on Indian regional dialects |
| Mid-Call Tool Calling Delay | <16ms (AI Speaks Without Pausing) | Halts audio synthesis during function run | 1.2s – 2.5s Dead Air | 1.8s – 3.5s Dead Air |
| Carrier Telephony Integration | Native Direct SIP Trunking & WebSockets | Third-party SIP/WebRTC bridge required | Twilio / Telnyx API wrapper | Twilio Reseller / Legacy PRI |
| Private VPC & On-Premises | 4-bit / 8-bit Quantized Weights (100% Air-Gapped) | Public Cloud API Only (No VPC/On-Prem) | Cloud SaaS Multi-Tenant Only | Cloud SaaS / Legacy Server Hardware |
| Cost Efficiency at Scale | $0.04/min (Transparent Flat Billing) | $0.06 – $0.24+/min (Tokens + Audio) | $0.08 – $0.15/min (Stack markup) | $0.09 – $0.20/min + High CapEx |
Ready to benchmark on
your telephony infrastructure?
Schedule a technical session with our speech research engineers and benchmark your live call flows with zero commitment.
