AI call monitoring

AI call quality monitoring software for QA teams

Move beyond sample-based reviews. KnownSense helps quality managers inspect more customer conversations, find risk faster, and coach agents with evidence from real calls.

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Built for

QA managers, contact center leaders, and operations teams that need consistent visibility into recorded customer calls.

call monitoring softwarecontact center quality assuranceAI call analysisconversation intelligence

India-first buyer context

Where this fits in a real call operation

For BPO owners and founders, AI call monitoring is most useful when it finds the handful of calls that explain customer escalations, agent drift, or missed process steps.

Common call examples

Inbound support calls
Outbound sales calls
Escalation calls
First-week agent calls

Rollout checks

Start with the call types where poor handling is most expensive.
Compare AI scores against a manager-reviewed sample before scaling.
Use flags for prioritization, then keep final QA judgment with humans.

Search intent

What teams want when they search for AI call quality monitoring software

Score calls against active QA rules and scorecards.

Detect moments that need supervisor review.

Turn transcripts and summaries into coaching follow-up.

Track quality trends across agents, teams, and call types.

Capabilities

A QA workflow that produces evidence, not just analytics

Automated scoring

Apply quality rubrics consistently so QA managers can review the calls that matter most.

Risk and quality flags

Surface compliance gaps, escalation signals, silence, profanity, and missed process steps.

Searchable call intelligence

Keep call summaries, transcripts, scores, and review context connected to the original conversation.

Workflow

From call recording to QA action

Upload or ingest recordings

Bring in audio from agents, supervisors, or worker pipelines.

Transcribe and score

KnownSense converts speech into structured QA signals and scorecard outcomes.

Prioritize review

QA teams focus on flagged calls, weak scores, and coaching opportunities.

Example evidence

A reviewable signal a manager can act on

KnownSense is designed to keep AI output reviewable: the manager sees the summary, score, transcript evidence, and the call record before taking action.

Signal to inspect

A support call is scored low because the customer issue was not summarized, the next step was unclear, and the call was flagged for supervisor review.

Decision it supports

The QA manager can inspect the transcript evidence, confirm whether the score is fair, and decide whether this is a coaching moment or a process gap.

Operating fit

Built around real QA jobs

Designed around QA manager workflows instead of generic analytics dashboards.

Supports scorecards, call flags, agent profiles, and training follow-up in one workflow.

Built for operational call centers that need auditability and repeatable review criteria.

FAQ

Questions buyers ask before a demo

What is AI call quality monitoring?

AI call quality monitoring uses transcription, language analysis, and QA rules to evaluate customer conversations and highlight the calls that need human attention.