CallQX — AI-Powered Call Intelligence

From recording to finalized review

Campaign-native AI call QA

Upload a call. AI transcribes it, scores it against that campaign’s policy, and cites the transcript. QA verifies, coaches, and finalizes — in one workspace.

Call evaluation · #4821

AI evaluation

Sales outreach · Policy matched

86
  • DisclosurePass
  • Script adherencePass
  • Empathy checkPass

Evidence from transcript

Agent

This call may be recorded for quality…

Customer

Okay, go ahead.

Live transcription

How it works

The full AI path, call by call

This is the same sequence the product runs: upload audio, transcribe with speakers, evaluate against the campaign scorecard, ground every finding in the transcript, then let QA close the loop. Play it through, or click a step.

Call #4821 · Solar outreach
Uploaded

Upload calls

Audio files

Drop MP3, WAV, M4A — or choose a file.

Upload & process
  1. 01 · Uploaded

    Audio is attached to a campaign and an agent. The file is stored; processing is queued.

  2. 02 · Transcribing

    Speech-to-text splits speakers and timestamps so evidence can land on a real line, not a summary.

  3. 03 · Evaluating

    AI loads that campaign’s active policy and scores every criterion against the transcript.

  4. 04 · Needs review

    Findings, overall score, and evidence spans are ready. The call sits in the QA queue.

  5. 05 · Finalized

    A reviewer accepts or overrides, coaches the agent, and locks the score into reporting.

AI QA that follows your campaigns

Activate policies per campaign. Upload calls. Let AI score them — then let QA review with evidence, not a spreadsheet.

Transcribe

Call audio becomes a speaker-labeled transcript with timestamps — the substrate every later finding cites.

Live transcription

Evaluate

The campaign’s active scorecard grades greeting, disclosure, empathy, close, and the rest — automatically.

Policy ↔ call match
KPI Score Card
Policy doc
Call #4821
Scored live
3 policies active

Evidence

Each finding quotes the exact utterance and timestamp so QA can verify, not guess.

Evidence from transcript
Agent

This call may be recorded for quality…

Customer

Okay, go ahead.

Agent

I can email a written summary today.

Review

Override a result, leave coaching notes, finalize. Campaign and agent metrics update from that review.

AI evaluation
86
  • DisclosurePass
  • Script matchPass
  • EmpathyPass

Call center management, built in

Scoring only works if the workspace already knows the campaign, the agent, and the policy. CallQX is that workspace — not a scoring tool bolted on later.

  • CampaignsThe unit of work. Every call, policy, and agent assignment hangs off a campaign — Solar, Med, Insurance, and so on.
  • PoliciesUpload the scorecard you already use. Activate it for that campaign. AI evaluates against the document, not a generic rubric.
  • AgentsCreate call agents, assign them to campaigns (and teams), and attribute every recording to the person who took it.
  • TeamsGroup agents for ownership and reporting — team scores roll up from finalized reviews.
  • QA usersInvite-only reviewers who own the queue: verify evidence, override findings, coach, and finalize.

Campaign-native by design

Calls, policies, agents, and reviews all hang off campaigns — so AI QA matches how your call center actually runs. A Solar call is never scored with a Med script.

Policy ↔ call match
KPI Score Card
Policy doc
Call #4821
Scored live
3 policies active

AI scores against your policies

Disclosure, script, empathy, closing, and the rest — pass, partial, or fail, with an overall score driven by the active campaign scorecard. You upload the document; AI derives the criteria.

AI evaluation
86
  • DisclosurePass
  • Script matchPass
  • EmpathyPass

Evidence, not guesses

Reviewers click a finding and the matching transcript lines highlight and scroll into view. Optional: seek the recording to that moment. Coaching stays grounded in what was said.

Evidence from transcript
Agent

This call may be recorded for quality…

Customer

Okay, go ahead.

Agent

I can email a written summary today.

Hear every call as data

Upload call audio (MP3, WAV, M4A, and more). Get a clean, speaker-labeled transcript ready for policy-aware scoring — no manual tagging, no spreadsheet scorecards.

Live transcription

Admins run the workspace. QA closes the loop.

Two portals on the same origin. Agents are people whose calls get scored — they don’t log in.

Admin portal

Admin

  • Create campaigns, activate policies, manage agents and teams
  • Invite QA reviewers
  • Upload calls and watch the queue
  • Dashboard: volume, scores, compliance, leaderboards

QA portal

QA

  • Work the needs-review queue, filter by campaign
  • Open a call: audio, transcript, findings, evidence
  • Accept or override each finding with a reason
  • Coach the agent, then finalize

From campaign setup to finalized review

Stand up the workspace once. After that, every recording follows the same path — campaign policy in, coached agent out.

  1. 01

    Set up

    Create campaigns, upload and activate scorecards, assign agents and teams, invite QA.

  2. 02

    Upload

    Drop call audio with campaign + agent. Processing starts: transcribe, then evaluate.

  3. 03

    AI evaluates

    Campaign policies score the transcript. Every finding ships with quoted evidence.

  4. 04

    QA finalizes

    Reviewers override if needed, coach the agent, lock the review. Metrics update.

Run QA the way your campaigns run

Create an org, set up campaigns and policies, invite QA — then upload your first call and watch it move from audio to a finalized review.