High volume needs
high consistency
Call centers run on volume. Manual QA covers 2 to 5% of calls. Tough Tongue AI covers 100% automatically, trains agents on real scenarios, and delivers instant feedback.
2-5%
Calls reviewed by manual QA
100%
Coverage with Tough Tongue AI
1-4
Score range flagged for human review
See the detailed workflow
Full API documentation, Python integration example, and extraction_vars configuration.
QA and training in one closed loop
Most platforms do QA or training. Tough Tongue AI connects them. Flagged calls become the basis for new training scenarios automatically.
100% call coverage via API or bot
- ✓ POST recordings or transcripts to REST API
- ✓ Deploy Note Taker bot for live Google Meet / Zoom
- ✓ Score triage: 1-4 for review, 5-7 acceptable, 8-10 archive as training material
- ✓ extraction_vars: pull sentiment, objection type, product mentioned from every call
Build agents from your real call data
- ✓ Upload worst calls so the AI learns what to avoid
- ✓ Upload best calls so the AI replicates top performer patterns
- ✓ Certify agents with MCQ knowledge tests before they go live
- ✓ Memory-enabled coaching: agents practice scenarios based on their scored weak spots
API endpoint: POST https://app.toughtongueai.com/api/public/v2/session
Score-based triage on every call
Every session is scored 1 to 10 against your rubric. Your QA team focuses on the 1-4s. Everyone else gets automated coaching.
1 - 4
Flagged for review
QA analyst reviews. Compliance risk, missed script, or significant coaching opportunity. Agent gets specific remediation training.
5 - 7
Acceptable
Agent gets automated post-call feedback. Tracked for trend analysis. Human review triggered only if a pattern emerges.
8 - 10
Model calls
Archived as training material. Used to auto-generate new practice scenarios that teach other agents what good looks like.
Frequently asked questions
Can this replace my existing QA team?
No, and it shouldn't. The goal is to free your QA analysts from listening to low-risk calls (scored 5 to 10) so they focus exclusively on flagged sessions (scored 1 to 4). You get 100% coverage with human attention concentrated where it matters most.
What call formats does the API accept?
MP3, WAV, M4A, MP4, and WebM. You can also submit raw transcripts as text. Both recording_url and transcript fields are supported. The API accepts batch uploads with metadata so you can process thousands of calls and filter by team, campaign, or date.
How do I extract structured data from calls automatically?
Configure extraction_vars in your scenario: define fields like customer_sentiment (list: positive/neutral/negative), objection_type (text), product_mentioned (boolean), compliance_language_used (boolean). These are extracted from every call and returned alongside the score, ready for your BI or CRM pipeline.
How does the Note Taker bot work?
The Note Taker bot joins your live Google Meet or Zoom sessions automatically. It captures the conversation, runs your QA rubric in real time, and delivers a scored report without anyone on your team needing to listen to a recording afterward.
Can agents practice with scenarios built from real call recordings?
Yes. Upload your best and worst call recordings. The AI analyzes them and generates practice scenarios that mirror your actual customer interactions, the exact objections, the exact scripts, the exact moments where agents go off-track.
How fast can we onboard a new wave of agents?
Using Courses, a new agent cohort can complete a structured onboarding path (product knowledge MCQs, script certification, and live conversation simulations) at their own pace, with automatic score-gating before they go live. No facilitator needed.
Move from 5% to 100% call coverage
Catch every compliance gap. Coach every agent. No extra headcount required.