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Overview

Zild Coach provides structured conversation evaluation for both AI agents and human operators. It analyzes:
  • Conversation transcripts
  • Agent decisions
  • Tool usage
  • Escalation handling
  • Policy adherence
  • Response clarity
Zild Coach converts qualitative conversations into quantifiable performance indicators.

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Architecture

Zild Coach operates on top of the Zild event and transcript system. Conversation → Transcript → Evaluation Engine → Scoring Model → Feedback Output

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1. Transcript Analysis

Every conversation (text or voice) produces a transcript. Zild Coach evaluates:
  • Response relevance
  • Instruction adherence
  • Escalation timing
  • Data capture completeness
  • Tone consistency

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2. Evaluation Engine

The evaluation engine applies:
  • Defined scoring criteria
  • Policy checks
  • Behavioral rules
  • Performance benchmarks
Evaluations can be:
  • Automatic (AI-based)
  • Rule-based
  • Hybrid (AI + deterministic checks)

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3. Scoring Output

Each evaluated conversation may include:
  • Overall score
  • Category breakdown
  • Strengths
  • Improvement suggestions
  • Policy violations (if detected)
Scores can be aggregated across:
  • Agent
  • Group
  • Channel
  • Time period

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Enterprise Governance

Zild Coach supports:
  • Quality assurance programs
  • Compliance monitoring
  • AI instruction validation
  • Human performance tracking
  • Continuous improvement cycles
It ensures AI systems remain aligned with operational standards.