Real-world walkthrough

See Scripts and Customer Intelligence work together

Follow one fictional customer journey from an adapted compliance script and a flagged call to a relationship brief, source-linked timeline, and clear next action.

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Built for

Clients, QA leaders, and compliance teams evaluating how KnownSense turns script rules and customer call history into reviewable operational decisions.

customer intelligence examplecompliance script templatecall script workflowsource-linked call analytics

India-first buyer context

Where this fits in a real call operation

This fictional collections journey shows how one published script checks an individual call while Customer Intelligence connects the promises, risks, and next action across the customer's full call history.

Common call examples

  • Collections reminder
  • Fee-dispute follow-up
  • Compliance exception
  • Payment-plan confirmation

Rollout checks

  • Treat each built-in pack as an editable starting point, not legal advice.
  • Dry-run and publish an approved version before routing it to live calls.
  • Keep AI answers linked to source calls and human review for important decisions.

Fictional client walkthrough

One risky call becomes a reviewable customer story

Northstar Finance and Meera Shah are fictional. The example mirrors the product workflow without exposing customer recordings, phone numbers, or tenant data.

Scenario

A collections team needs consistent fair-practice checks and a better handoff between agents.

Script used
Adapted collections fair-practice copy, v3
Evaluation result
62% adherence, one critical review
Manager action
Verify evidence, correct language, protect the next callback

Call evaluation

09 Jul, outbound collections call

Human review needed
01

Identify the agent and organization

RequiredHybridMet

“My name is Kavya, calling from Northstar Finance.”

02

Verify the customer before account details

RequiredSemanticMet

“May I confirm I am speaking with Meera Shah?”

03

No threats, pressure, or third-party disclosure

ForbiddenSemanticReview

“Our field team may visit your office and speak to your manager.”

04

Offer a practical repayment option

RecommendedSemanticMet

“I can request two instalments if that is easier.”

05

Confirm the next action, owner, and date

RequiredSemanticMissed

No clear callback owner or date was confirmed before the call ended.

How Scripts work

A controlled rule lifecycle, not a static prompt

Each script combines ordered checks, rule type, matching mode, weight, criticality, and evidence guidance. Publishing freezes a version for future calls while keeping previous results traceable.

  1. 01

    Install

    Choose a built-in pack or start from a blank script.

  2. 02

    Adapt

    Edit the private workspace copy to match approved policy and call types.

  3. 03

    Dry-run

    Test a sample transcript and inspect status, confidence, evidence, and timestamps.

  4. 04

    Publish

    Create a versioned rule set so later edits do not rewrite past results.

  5. 05

    Route

    Apply the published version to everyone, one QA group, or one agent.

  6. 06

    Review

    Inspect critical misses, verify source evidence, and override AI output when needed.

Required checks are expected on applicable calls.

Forbidden checks surface language that may need review.

Recommended checks support coaching without becoming hard failures.

Customer Intelligence

The call is one event. The relationship is the decision context.

A phone-number lookup assembles matching calls into a source-linked timeline. The relationship brief and AI answers stay bounded to those calls, so managers can verify each claim.

Relationship brief

Meera Shah · ••••••1842

High attention
Current state
Two-instalment plan accepted in principle. The disputed fee and written confirmation remain open.
Next best action
Supervisor callback with the fee decision, written plan, named owner, and due dates.

  1. 02 Jul

    Call 1

    Payment reminder

    Kavya RaoNeutral

    Customer said the full payment was not possible this week and asked whether instalments were available.

  2. 05 Jul

    Call 2

    Fee dispute

    Rohan MehtaFrustrated

    Customer disputed a late fee. The agent promised that billing would review it and call back within two working days.

  3. 09 Jul

    Call 3

    Escalation

    Kavya RaoNegative

    No callback had arrived. The collections conversation included language that needs compliance review.

  4. 11 Jul

    Call 4

    Recovery plan

    Aisha KhanImproving

    Customer accepted a two-instalment plan in principle, subject to written confirmation and resolution of the disputed fee.

Ask Customer AI

What did we promise, and what is still open?

Billing promised a fee review and callback within two working days. That callback was missed. The customer later accepted two instalments in principle, but still needs the fee decision and a written plan with dates.

Call 2, 05 Jul Call 4, 11 Jul

Pre-built compliance packs

What is inside the current starter library

Each pack installs as an editable workspace copy. Teams can inspect every check before installation, then change labels, intent, phrases, weights, criticality, and applicability before publishing.

These templates are operational starting points, not legal advice. Your compliance owner should approve the final script and review policy.

01

TRAI telesales consent and identity

Telecom · 3 checks

  • Agent identifies organization
  • Gets permission to continue
  • No pressure after opt-out
02

RBI collections fair practices

Collections · 3 checks

  • Collector identity disclosed
  • No threats or intimidation
  • Repayment options explained
03

IRDAI insurance suitability and disclosure

Insurance · 3 checks

  • Customer needs confirmed
  • Key limits disclosed
  • No guaranteed return claims
04

SEBI advisory disclosure

Advisory · 3 checks

  • Market risk disclosed
  • Suitability checked
  • No profit guarantee
05

KYC verification security protocol

Security · 3 checks

  • Verification purpose disclosed
  • No full secret requested
  • Next step confirmed

Route one published script to a tenant, QA group, or individual agent.

Version history keeps the rule context attached to calls scored at that time.

Evidence and timestamps let a reviewer verify important matches and misses.

Search intent

What teams want when they search for call script compliance example

See the fields and rule types inside a practical call script.

Understand how a script moves from install to publish, routing, and review.

Inspect what is included in every current pre-built compliance pack.

See how Customer Intelligence connects promises and risks across source calls.

Capabilities

A QA workflow that produces evidence, not just analytics

Editable, versioned scripts

Install a starter pack, adapt the private copy, dry-run it, and publish an approved version for future calls.

Reviewable call evidence

Each result can carry status, confidence, transcript evidence, and a timestamp so managers can verify important signals.

Customer-level memory

A phone-number timeline brings related calls, open asks, promises, risk, next action, and source-linked AI answers together.

Workflow

From call recording to QA action

01

Publish the approved script

Start from a pre-built pack or blank script, adapt the checks, test a transcript, and publish a version.

02

Evaluate future matching calls

KnownSense checks required, forbidden, and recommended moments while retaining the supporting call evidence.

03

Act with relationship context

Customer Intelligence connects the individual result with earlier promises, repeated issues, and the next best action.

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 forbidden-language check surfaces a specific collections statement for human review, while the customer timeline shows the missed callback that increased risk before that call.

Decision it supports

The manager can correct the next conversation, resolve the open fee question, coach the agent, and retain the exact source-call trail behind the decision.

Operating fit

Built around real QA jobs

The public walkthrough uses fictional data and exposes no tenant or customer records.

Compliance templates install as editable copies and should be approved against each organization's policy.

AI signals stay reviewable through transcript evidence, source-call citations, and human override workflows.

FAQ

Questions buyers ask before a demo

Can we edit a pre-built compliance pack?

Yes. Installing a pack creates an editable workspace copy. Authorized users can change its checks, save a draft, dry-run the changes, and publish a new version.

What does a script check?

A script can check required, forbidden, or recommended conversation moments using phrases, semantic intent, or hybrid matching, with weights and criticality for each step.

Does Customer Intelligence search public customer data?

No. It works from the tenant's own matching call history and keeps AI answers linked to those source calls. The example on this page is entirely fictional.

Keep exploring

Related pages

View all resources

Features

Script compliance

Monitor whether agents follow required, forbidden, and recommended call script steps for regulated or process-heavy conversations.

Read page

Solutions

Conversation intelligence

Use conversation intelligence to turn call recordings into transcripts, summaries, quality signals, compliance flags, and coaching insight.

Read page

Resources

Sample AI call quality report

See what a practical AI call quality report should include: score summary, transcript evidence, QA flags, coaching notes, and reviewer decisions.

Read page