Data Sources → Customer Touchpoints

Call Center

Voice interactions through the contact center — call metadata, IVR selections, agent notes, and outcomes — usually sourced from a CCaaS platform.

High-Level Design

CCaaS export → Azure Blob Storage → .NET Core microservices on Azure.

Touchpoint

Call Center

Inbound/outbound voice via CCaaS

→

Ingestion

.NET Core Batch Connector

CCaaS export → Azure Blob Storage → Ingestion API

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Processing

.NET Core Batch Worker

Azure Functions — redaction, transcript enrichment

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Foundation

Data Lakehouse

Call metadata + linked transcripts

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Intelligence

.NET Core AI & Insights API

Azure OpenAI — topic modeling, CSAT prediction

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Activation

.NET Core Activation API

CRM case updates, agent coaching (Reverse ETL)

💼 Business Context

The highest-cost-per-interaction channel — connecting it to CXOS ties call outcomes to lifetime value and churn risk
Enables agent coaching and QA automation at scale instead of manual sampling
Owned by Contact Center Operations, often co-funded by CX Analytics

🔌 Technical Overview

CCaaS platforms (Genesys, NICE, Five9) export call metadata and recordings to Azure Blob Storage on a schedule; a timer-triggered .NET Core Azure Function picks up new files and calls the Ingestion API through Cxos.Ingestion.Client — the same contract as every real-time touchpoint. Recordings are transcribed and redacted (PCI/PII) by a .NET Core batch worker before the transcript is attached to the call record. Caller ID or an IVR-entered account number is matched to a known customer profile via the Identity API.

Typical Events

call_started ivr_selection call_transferred call_ended csat_recorded

💾 Sample Event Payload

{
  "event": "call_ended",
  "event_id": "a4d1c9e2-5b8f-4a3e-9c1d-7e2f8a0b4d56",
  "timestamp": "2026-08-01T11:03:12Z",
  "user_id": "cust_004821",
  "context": {
    "channel": "call_center",
    "agent_id": "agt_302",
    "queue": "billing"
  },
  "properties": {
    "duration_seconds": 342,
    "disposition": "resolved",
    "csat_score": 4
  }
}

🔗 Integration Points

Azure Blob Storage — CCaaS export landing zone
Timer-triggered Azure Function (.NET Core) — batch pickup and Ingestion API call
Cxos.Ingestion.Client NuGet package — shared ingestion contract
Azure OpenAI Service — transcript topic/sentiment modeling
Reverse ETL — CRM case sync via the Activation API

⚠️ Non-Functional Considerations

Scale: call volume spikes correlate with outages/incidents — the batch pipeline is decoupled from real-time load
Latency: most call analytics run as scheduled batch (hourly); escalation-risk flags use a near-real-time path where the CCaaS platform supports it
Reliability: the batch worker supports reprocessing/backfill when the redaction model is updated
Security/Privacy: PCI redaction runs before the transcript reaches the Data Lakehouse; the Blob landing zone uses short retention + Azure Key Vault-managed encryption

🎯 Enterprise Example

A financial services contact center exports call metadata and recordings to Azure Blob Storage nightly. The .NET Core batch worker redacts PCI data and calls the AI & Insights API, backed by Azure OpenAI Service, which surfaces a rising cluster of "fee dispute" calls tied to a recent statement change — reaching the product and billing teams within a day instead of the next quarterly QA review, and cutting related call volume by 22% within two weeks.

← Back to Customer Touchpoints