Transcript-Based Classification

Uncover Hidden Risks in Customer Interactions

Complaints are often buried in thousands of hours of calls, chats, and emails. This AI Agent autonomously classifies conversations, tracks emerging themes, and correlates risks to prevent customer harm.

🔍

Detect

Identify complaints and potential harm in unstructured text.

📈

Track

Monitor emerging complaint themes in real-time.

🛡️

Mitigate

Proactive UDAAP and conduct risk reduction.

1. Intelligent Conversation Analysis

The core function of the AI Agent is to ingest raw transcripts (Voice-to-Text, Chat logs) and classify them. Test the agent below by processing the queue of incoming customer interactions. Watch how it extracts intent and risk signals.

Incoming Interaction Queue

5 Pending

AI Analysis Output

⚡

Waiting for input stream...

Emerging Complaint Themes

Real-time volume tracking by category. The AI aggregates individual tags into broader trends.

Risk Correlation & Conduct

Correlating complaints with specific products and channels to identify systemic issues.

Strategic Outcome: Proactive Risk Mitigation

By automating the classification of complaints and harm markers, the organization moves from reactive fire-fighting to proactive prevention. This directly supports UDAAP (Unfair, Deceptive, or Abusive Acts or Practices) compliance.

100%

Coverage

Of calls and chats analyzed, vs 2-5% with manual QA.

-40%

Escalation Time

Faster identification of "Harm" triggers allows immediate intervention.

High

Conduct Visibility

Clear correlation of complaints to specific agent behaviors.