Case study

Automated Customer Reporting From Contact-Center Data

Customer ReportingContact Center AnalyticsWorkflow OrchestrationAI AnalysisPDF GenerationAI Quality EvaluationClient: BaltoAI Automation & Documents

Call-related data turned into recurring customer reports.

The challengeRepeated analysis and customer-report preparation.

The solutionScheduled reporting with an AI quality checkpoint.

Aggregated call data feeds findings and recommended actions.

PDF reports become available through the Balto Dashboard.

Approximately 9,800 customer reports per month reported.

Engagement

Overview

Balto needed a repeatable way to turn contact-center data into customer reports. The workflow had to connect data analysis with findings, recommended actions, and a report recipients could download.

I built a reporting pipeline that starts with an automated scheduler. Each report job enters a workflow that aggregates and analyzes call-related data, then uses the resulting aggregates and anomalies to support AI-generated findings and actions. Those outputs feed PDF report generation.

Draft reports pass through an AI report-quality checkpoint that uses a language-model endpoint for quality evaluation. Reports approved by that checkpoint are stored and made available through the Balto Dashboard, connecting generation to customer delivery.

Usage figures are internally reported. Reporting periods and user definitions remain unconfirmed.

Reported users: 480
Reported customer reports / month: ≈9,800

Scheduled analysis feeds AI findings and PDF generation, followed by an AI quality checkpoint and dashboard delivery.

Challenge

Customer reporting needed an end-to-end process, not only a generated narrative.

Recurring production
Report jobs needed to run through a scheduled workflow.
Data interpretation
Call-related measures needed to become findings and recommended actions.
Quality evaluation
Draft reports needed a checkpoint before becoming available to recipients.
Delivery
The workflow needed to include PDF generation, report storage, and dashboard download.

Solution

I connected scheduling, data analysis, AI interpretation, and report delivery.

Automated scheduling
Start report jobs through a scheduler.
Aggregation and analysis
Process call-related data into aggregates and anomalies.
Findings and actions
Use the analysis context to support AI-generated findings and recommended actions.
PDF generation
Package the findings and actions into report documents.
AI quality evaluation
Send draft reports through the documented AI report-quality checkpoint.
Dashboard delivery
Store checkpoint-approved reports and make them available for download.

From analysis to delivery

The workflow continues after the model produces findings. PDF generation, quality evaluation, storage, and dashboard access are separate stages in making the report available to a customer. The checkpoint is an AI evaluation step, not a claim of human sign-off or guaranteed correctness.

Impact

Reported volume shows recurring customer-reporting activity through a connected generation and delivery workflow.

Reported adoption
480 users.
Reported activity
Approximately 9,800 customer reports per month.
Implemented capability
Scheduled analysis, AI findings, PDF generation, AI quality evaluation, and dashboard delivery.

Tools & Technologies

Workflow orchestrationAutomated schedulingCall-data aggregationLanguage-model analysisAI report-quality evaluationPDF generationReport storageBalto Dashboard