Use Case

Stop reviewing 3% of calls. Review all of them.

Manual QA teams cover 2 to 5% of calls. Tough Tongue AI covers 100%, automatically scored against your rubric, with structured data extracted from every session.

Try it free

2-5%

Calls reviewed by manual QA teams

100%

Coverage with Tough Tongue AI

0

Blind spots in your call data

Triage every call automatically

Every session is scored 1 to 10. Your team only touches the calls that need a human eye.

1 - 4

Flag for review

Sent to a human QA reviewer. These are the calls with compliance risk, missed scripts, or significant coaching opportunities.

5 - 7

Acceptable

Logged and tracked. Rep gets automated feedback. No immediate human review needed unless a pattern emerges over time.

8 - 10

High performers

Flagged as top-performer recordings. Archive these as training material and use them to auto-generate new practice scenarios.

Two ways to capture calls

Fits your existing infrastructure, whether you have recordings already or need a bot to capture live sessions.

Option A: Upload via API

POST recordings (MP3/WAV/M4A/MP4/WebM) or transcripts to our REST API. Works with any telephony platform, CRM, or call recorder you already use. Batch upload historical recordings, tag with metadata, and retrieve scored results programmatically.

POST https://app.toughtongueai.com/api/public/v2/session
{ scenario_id, recording_url,
  user_email, metadata }

Option B: Note Taker Bot

Invite the Tough Tongue AI bot to join your Google Meet or Zoom sessions. It listens, captures the conversation, runs your QA rubric, and delivers a scored report automatically. No manual recording download required.

  • Works with Google Meet
  • Works with Zoom
  • Automatic post-call scoring
  • Zero extra steps for reps

Integrate in minutes with our API

Upload a recording, trigger analysis, and poll for scored results. Here's a complete Python example.

quality_audit.py 
import requests
import time

API_KEY = "your-api-key"
BASE = "https://app.toughtongueai.com/api/public"

# Upload a recording
session = requests.post(f"{BASE}/v2/session", json={
    "scenario_id": "your-scenario-id",
    "recording_url": "https://storage.example.com/calls/call-123.mp3",
    "user_email": "rep@company.com",
    "metadata": {"team": "east-coast", "campaign": "q1-2026"}
}, headers={"Authorization": f"Bearer {API_KEY}"}).json()

# Trigger analysis
requests.post(
    f"{BASE}/v2/sessions/{session['id']}/post-process",
    json={"run_analysis": True, "run_extraction": True},
    headers={"Authorization": f"Bearer {API_KEY}"}
)

# Poll for results
while True:
    result = requests.get(
        f"{BASE}/v2/sessions/{session['id']}",
        headers={"Authorization": f"Bearer {API_KEY}"}
    ).json()
    if result.get("evaluation_score") is not None:
        break
    time.sleep(5)

# Triage
score = result["evaluation_score"]
if score <= 4:
    print("Flag for human review")
elif score <= 7:
    print("Acceptable, send automated feedback")
else:
    print("Archive as training material")

Extract structured data from every call

Configure extraction_vars in your scenario to pull specific fields from every session. Use them for filtering, dashboards, and automated triage.

extraction_vars config 
{
  "extraction_vars": [
    {
      "name": "customer_sentiment",
      "type": "list",
      "options": ["positive", "neutral", "negative"]
    },
    {
      "name": "objection_type",
      "type": "text"
    },
    {
      "name": "product_mentioned",
      "type": "boolean"
    },
    {
      "name": "compliance_language_used",
      "type": "boolean"
    }
  ]
}

Tools to get started

Scenario Creator

Build your QA rubric with custom scoring criteria and extraction variables. Describe what you're looking for and the AI builds the rest.

Google Meet Agent Docs

Set up the Note Taker bot to automatically join your team's Google Meet sessions and deliver scored reports.

Frequently asked questions

Can this replace my existing QA team?

No, and it shouldn't. The goal is to free your QA team 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 audio and video formats does the API accept?

The API accepts MP3, WAV, M4A, MP4, and WebM. You can also submit raw transcripts as text if you already have a transcription pipeline. Both recording_url and transcript fields are supported in the same endpoint.

How do I triage high-risk calls automatically?

Configure extraction_vars in your scenario to pull structured fields from every call: customer sentiment, product mentioned, objection type, compliance language used. Your backend can then filter and prioritize based on these extracted values alongside the numeric score.

What's the Note Taker bot and how does it work?

The Note Taker is an AI bot that joins your live Google Meet or Zoom calls automatically. It captures the conversation, runs your QA rubric against it in real time, and delivers a scored report without anyone on your team having to listen to the recording.

Do reps get individual coaching from audit results?

Yes. Each scored session includes a rep-facing report with criteria-level breakdowns, transcript citations, and specific suggestions for improvement. Reps can review their own performance without needing manager involvement.

Is there a way to batch upload historical recordings?

Yes. The bulk processing endpoint accepts batched uploads with metadata tagging (e.g. team, campaign, date range) so you can process weeks of historical calls and filter results by any dimension you care about.

Stop guessing what's happening on your calls

100% call coverage, automated triage, and rep coaching, all from one platform.

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