AI Voice Suite
Real-time voice AI for contact-center teams — screen candidates and coach agents, all in a natural US-accent voice. Choose a module to begin.
›AI Voice Hiring
Customer Support Associate (Voice)
📍 Radius gate:
🎯 Advance ≥
🕘 Calls · retry h
Candidate resumes
Upload resumes, or load the sample set to run screening.
Screening results
Location is a hard gate. Only candidates in-radius AND above threshold advance to an AI call.
| Candidate | Location | Distance | Gate | Score | Outcome |
|---|
Scheduled interviews
AI voice interviews for candidates who cleared screening. Calls run inside the configured window; no-answer auto-retries.
🎙️
Interview
Ready. Click Start Interview and allow the mic. Emma will greet the candidate first.
Candidate scorecard
Highlights
Concerns
Transcript
⬇ A .txt copy was downloaded automatically.
Hiring analytics
Recruiter funnel — independent of coach.
Recent candidates
| Name | City | Distance | Score | Outcome |
|---|---|---|---|---|
| No data yet. | ||||
›AI Voice Coach
Choose a practice call
Pick a customer persona and the training phase. Scoring adapts to the phase's targets.
Coach analytics
Agent practice performance — independent of hiring.
By phase
Team impact projection
If every below-target session in this data were lifted to its phase's QA target via the Evaluate → Coach → Train → Retest loop.
Recent sessions
| Persona | Phase | QA | Result |
|---|---|---|---|
| No sessions yet. | |||
🎧
Customer
⏱ First-response window: 10.0s — respond before it hits zero
Ready. Click Start Call and allow the mic. The customer will speak first — respond promptly.
Session Scorecard
💡 Coaching notes
Strengths
Focus next
Transcript
⬇ A .txt copy was downloaded automatically.
Personalized training plan
Pre-training baselineCoaching opportunities identified
Recommended microlearning
Modules shown here are placeholder titles for this demo — in production, these route to your real content/LMS and are assigned automatically.
Improvement report
By coaching dimension — before → after
›Trainer
Trainer sign-in
Select your name to see your own batch dashboard.
Demo-only identity select — no password. Production would use real trainer accounts via SSO/roster, scoped so each trainer only ever sees their own batches.
My batches
Your NHT batches, practice trend, and how they carried into production.
My batch avg practice score — month on month
My batches
Click a batch to see its trainees.
| Batch | Start | Certified | Size | Avg NHT score | Status |
|---|
My NHT → Production linkage
How your batches' practice scores carried into production QA after certification.
| Batch | Avg NHT score | Avg production score | Δ practice → production |
|---|
Batch
Trainees
Click a trainee to see their practice sessions by phase.
| Trainee | Sessions | Avg NHT score | Status |
|---|
Trainee
›Admin
Admin sign-in
Enter the trainer PIN to configure the demo.
Demo PIN: 0000
Admin Configuration
All settings below are editable and drive the live demo.
Phase KPIs & QA targets
Three lifecycle phases, each with its own targets. Edit any cell.
| Parameter | New Hire Training | Nesting 0–30 days | Production >30 days |
|---|
Fatal QA rule
Auto-fail conditions applied to every scored session.
If the agent does not respond within this many seconds of the customer's first line, the session is an automatic fail regardless of other scores.
NHT Batch Performance Dashboard
Batch-wise practice performance, month-on-month trend, and linkage to production results.
Batch, trainer, and production-linkage figures below are illustrative fixtures for this demo. A production build would pull batch rosters from your LMS and production QA from your live scoring pipeline.
Batch avg practice score — month on month
Average NHT practice score of batches started in each month.
Batch-wise average scores
| Batch | Trainer | Start | Certified | Size | Avg NHT score | Status |
|---|
NHT → Production score linkage
Same batch, compared: average practice score during NHT vs. average production QA score after certification.
| Batch | Trainer | Avg NHT score | Avg production score | Δ practice → production |
|---|
Trainer-wise KPI comparison
Each trainer's batches vs. the team average for this date range.
| Trainer | Batches | Avg NHT score | vs team | Avg production score | vs team |
|---|
Job description
What the AI recruiter screens against.
Screening rules
Gate + threshold used to decide who gets an AI call.
Location is a hard gate (non-negotiable). Calling window keyed to candidate-local time; 9–18 sits inside the US 8am–9pm baseline. Age/birth-year is verification only, never scored.
Interview questions
The AI recruiter weaves these conversationally.
Recruiter voice & notes
Persona and special instructions for the AI recruiter.