Application Layer — Customer Engagement

Conversational Analytics

Turns every customer conversation — chat, voice and email — into structured, searchable insight.

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Built on Foundation Layer
AI Governance & Observability, Enterprise AI Gateway
The problem

What breaks without this

  • Insight from customer conversations is trapped in unstructured transcripts and call recordings.
  • Emerging issues are noticed only after they generate a spike in complaints.
  • Manual quality review can sample only a small fraction of total conversation volume.
In one paragraph

Analyzes conversation transcripts across chat, voice and email for sentiment, topic trends, resolution outcomes and emerging issues, giving support, product and marketing teams a structured, ongoing view of what customers are actually saying.

Capabilities

What it does

Topic and intent extraction across chat, voice and email transcripts at full volume.

Sentiment and emotion tracking over time, by channel, product line or agent.

Automated quality scoring against defined conversation standards.

Emerging-issue detection that flags topic spikes before they show up in aggregate complaint metrics.

Dashboards and exportable reports for support, product and marketing stakeholders.

How it works

From request to result

01

Ingest

Transcripts from chat, voice and email conversations are ingested continuously.

02

Analyze

Topic, sentiment and quality scoring are applied to every conversation, not a manual sample.

03

Detect

Trend and anomaly detection flags emerging topics or quality drops.

04

Report

Findings surface through role-specific dashboards for support, product and marketing teams.

Governance & security

Built to be audited, not just used

  • Personally identifiable information is redacted from analytics views not requiring it.
  • Agent-level quality scores are used within existing performance-review governance, not as an unreviewed automated verdict.
Integrates with

Fits existing infrastructure

AI Chatbot Platform AI Voice Agent AI Customer Support Business intelligence tooling
What changes

Outcomes to expect

Qualitative, directional outcomes. We do not publish unverified performance figures — see the case studies section for engagement-specific, authorized results.

  • Emerging product and service issues are identified earlier.
  • Quality review coverage extends to the full conversation volume, not a sample.
  • Product and marketing teams get a direct, structured feed of customer language and concerns.
Related

Works alongside

Customer Engagement

AI Customer Support

Resolves support tickets across channels using product knowledge, account context and defined resolution actions.

 Customer Engagement

AI Chatbot Platform

Deploys grounded, brand-consistent conversational agents across web, mobile and messaging channels.

 Operations & Analytics

AI Analytics

Answers business questions in natural language against live operational and financial data.

Evaluate Conversational Analytics for your environment

Talk to an architect about integration into your existing stack, or request a scoped demo against a representative use case.

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