naviai Financial AI · Quality Inspection

Every call,
compliant and traceable.

“How do you make sure every single call meets quality and compliance standards? That is the core question of voice quality inspection.”
100% recording inspectionEvery call recorded and checked — no blind spots, reviewable at any time.
AI compliance judgementSensitive words and non-compliant scripts caught in real time, risk stopped on the spot.
Book a QA demo Follow a call's journey →
of calls and chats inspected, not sampled
0%
Semantic matching while the agent speaks
ms-level
Inspection modes: offline and real-time
0
Real-time layers: ear, brain, hand, eye
0

A call's journey

The quality-inspection loop: after the call, and during it.

Offline inspection checks every recording for compliance after the call. Real-time inspection listens while the agent speaks and stops violations before they land.

Offline inspection: compliance checks after the call

  1. ASR transcriptionTurns call recordings into text
  2. Semantic recognitionAI analyses what was said and why
  3. Rule matchingChecks against the compliance knowledge base to find risk
  4. QA ticket generationArchives automatically and drafts corrective advice

Real-time inspection: checked as it's said

Core value: stop violations during the call and cut compliance risk

  • Ear (listen)Real-time voice-stream capture
  • Brain (think)Millisecond semantic analysis
  • Hand (control)Blocks or flags violations instantly
  • Eye (watch)Live pop-up prompts on the agent's screen

That completes a call's journey. From dialling to inspection, the platform makes dozens of decisions across many system modules — so that every interaction is compliant and efficient.

Offline inspection

Every recording and every chat, inspected end to end.

From the call-record centre to naviai-qc and back, then through our in-house machine inspection and human review — the full offline pipeline in three views.

Third-party integration
Quality-inspection platform
Call-record centre
Message listener
Request assembly
QA request table
Text-model transcoding
naviai adapter · submit
Message listener
QA request table
Callback adapter
Result query
Encryption service
ASR engineLLM · via AI Gateway
Ticketing system
Big data
KafkaCloud
naviai-qc
naviai-qc
RocketMQCloud
RocketMQ save encrypt / decrypt HTTP callback update inspection-done event rule hit HTTP

Supported business scenarios

Voice inspection
  • All collections calls
  • All telesales calls
  • All customer-service calls
Text inspection
  • All collections chats
  • All customer-service chats

Real-time inspection

Inspection while the agent is still talking.

Live call audio is mirrored without touching the call, transcribed in real time, matched against your QA configuration within milliseconds, and pushed straight to the agent's screen.

Mid-platform QA system
Agent client
SDK integration
Business system
Mid-platform telephony
  • Voice channel
  • Voice events
Telephony vendor
Voice entity
Business API
  • Organisation
  • User
  • Token
Session API
  • Start session
  • End session
Agent lookup
Traffic filteringcontinuous QA
Real-time QA systemcontinuous QA
① org & user · get token call ② event relay place call ③ call-state sync traffic mirroring agent lookup transcription ④ HTTP transcript echo

Supported business scenarios

Voice inspection
  • Collections
  • Telesales
  • Customer service

Real-time architecture, abstracted

Ear, brain, hand, eye: four layers that make live QA work.

01 · EAR

Perception layer

Building the ability to listen · data intake

Turns telephony signals into an analysable text stream.

Mechanism
Traffic mirroring plus real-time ASR — non-intrusive data capture.
What it does
Hides differences between underlying telephony protocols and outputs one standard voice-to-text stream as clean fuel for the layers above.
02 · BRAIN

Decision layer

The core that thinks · real-time computing

Rule matching and risk judgement within milliseconds.

Mechanism
MQ message-driven + Redis cache + stream computing
What it does
  • Session management — keeps call context alive: init, buffer, end
  • Real-time matching — streams transcripts against the QA config and raises violation alerts
  • State aggregation — combines multi-turn results into one complete QA profile
03 · HAND

Execution layer

Reaching the frontline · result push

Pushes QA conclusions to frontline terminals in real time.

Mechanism
WebSocket long connections + global broadcast
What it does
  • Low-latency delivery — the agent's client receives the prompt the moment the script is spoken
  • Precise routing — extension number and callId deliver each result to the right agent: checked as it's said
04 · EYE

Closed-loop layer

Watching everything · management & review

A full loop from live monitoring to after-the-fact review.

Mechanism
Asynchronous batch consumption + persistent storage + management console
What it does
  • Data retention — conversations and QA results stored for historical tracing
  • Human review — inspectors correct machine misjudgements and feed models back
  • Panoramic view — one QA management centre for the quality of every interaction

Inspect every call, not a 3% sample.

Bring a batch of recordings or a live line. We'll configure your compliance rules, run offline and real-time inspection side by side, and show you the results in the QA workbench.

What the demo covers

  1. Configure inspection, scoring and review rules
  2. Run offline inspection on your own recordings
  3. See a live call flagged on the agent's screen
  4. Human review, appeals and integration plan
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