Your Voice AI plagued by
Lag · Hallucinations · Robotic Conversations?
Where Voice Agents Actually Break
If you've been building voice AI, you've hit at least a few of these.
Speech & Understanding
- ▸STT crumbles on real telephony audio
- ▸Regional accents and code-switching misfire
- ▸Brand names transcribe differently every call
Latency & Flow
- ▸3+ second pauses kill conversations
- ▸Agent interrupts when users pause to think
- ▸Backchannel signals trigger false interruptions
LLM Behavior
- ▸Agent hallucinates details the user never said
- ▸Negative feedback misread as goodbye
- ▸No structured data extraction from conversations
Telephony & Ops
- ▸SIP errors silently marked "completed"
- ▸No per-call cost tracking
- ▸Can't tell stale numbers from carrier issues
You Don't Start From Zero
Every deployment inherits years of production learnings — You get months of compounded tuning from day one.
Turn detection tuned, interruption thresholds calibrated
Deployed across tens of thousands of real calls — not synthetic benchmarks
100+ regression tests built from real production failures
Ship prompt changes with confidence.
New deployments adapt to domain and carrier in days
Not months — because the hard parts are already solved
Modular stack you own — not locked into any platform
Swap STT, LLM, or TTS providers as the market evolves
Optimise costs to as low as $0.01 per minute
Full visibility into per-call spend across every component
Trusted by Industry Leaders
See what our clients say about their experience working with our senior engineering team
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