Real-time Voice AI Monitoring

Your voice AI is failing.
You just can't see it.

Voice AI doesn't throw 500 errors when it hallucinates. No stack traces when latency spikes. No alerts when RAG goes stale. VoxLint gives you eyes on the full pipeline — and the reflexes to stop failures before they reach users.

STT → LLM → RAG → TTS
Sub-second detection latency
Auto-halt on hallucination
Voice AI pipeline monitoring dashboard
STT: 142ms
LLM: 380ms
RAG: 891ms ⚠
TTS: 210ms
The Problem

One bad response costs you the call.

Traditional APM sees servers. Not conversations. When your voice agent hallucinates a policy, invents a balance, or goes silent mid-sentence — your dashboard says everything is fine.

STT
Speech-to-Text
Accent drift
Silences misread
Overlapping speech
→
LLM
Reasoning Engine
Hallucinations
Off-script responses
Instruction drift
→
RAG
Knowledge Retrieval
Stale embeddings
Wrong context retrieved
Retrieval timeout
→
TTS
Voice Synthesis
Clipping / truncation
Pronunciation errors
Tone inconsistency

Every stage is a failure point. VoxLint monitors all of them.

Hallucination detection visualization
Detection

Catch hallucinations the moment they form.

LLM-based judges analyze every response against retrieved context — in real time, not post-call. When the agent says something unsupported by your knowledge base, VoxLint flags it instantly.

  • ◉ Ontology-grounded retrieval checking (OGAR)
  • ◉ Per-turn confidence scoring with trace replay
  • ◉ Gibberish detection, interruption tracking, sentiment shifts
  • ◉ Custom LLM judges you define in plain language
01

Detect

Real-time scoring across STT accuracy, LLM faithfulness, RAG relevance, and TTS quality. Alerts fire before the response reaches the caller.

02

Halt

On hallucination or SLA breach, VoxLint can interrupt the call loop — stop the response, log the full context, surface the root cause. No more silent failures.

03

Fix

Automated retry with corrected context. Fallback to human handoff when needed. Regression tracking to catch recurring failure modes.

04

Learn

Every incident feeds back into your eval suite. Prompt changes, model upgrades, and RAG updates are tested against the full failure corpus before shipping.

Not just observability. Closed-loop reliability.

Telemetry

Latency is a feature. See all of it.

Time to First Word
340ms
p50 across 1.2M calls
Turn-Taking Latency
210ms
p95 threshold: 800ms
Hallucination Rate
0.3%
vs 1.2% industry average
RAG Retrieval Time
89ms
p95 with fallback
Coverage
100%
every call, not sampled
Auto-halt Saves
847
bad responses in 30 days

Voice AI is critical infrastructure.
Stop flying blind.

Every hallucination that reaches a customer is a trust problem. Every latency spike is a dropout. Every silent failure is a problem you won't know about until the call review lands in your inbox.

VoxLint is the observability layer that actually protects your voice product — not after the fact, but in the moment.