AI Document Intake Automation

Template-based data extraction runs configured extraction templates directly on scored transcripts or customer documents. The system analyzes the text, identifies key fields according to your template configuration, and extracts structured data for downstream analytics, quality monitoring, and operational reporting.

In addition to documents, the platform supports quality assurance analysis and extraction across customer calls, chat transcripts, and email interactions. This broad interaction support allows quality assurance teams to maintain unified evaluation standards and capture structured data across diverse communication channels.

Automated extraction captures structured information from analyzed interactions and documents, turning routine quality reviews into actionable workflow insights. QA managers can track performance patterns, review metric-level explanations for interaction scores, and deliver targeted coaching to improve overall team performance.

Yes. The platform supports custom rubrics, metrics, and scoring weights for evaluating interactions and documents against specific quality standards. This flexibility allows contact centers and customer-facing teams to align AI scoring directly with internal operational criteria and compliance guidelines.

AI post-analysis extraction and classification features are included with unlimited feature usage on the Pro plan at eighty-nine dollars per agent monthly, whereas the Essentials plan provides entry-level scoring options at forty-nine dollars per agent monthly without extraction workflows.

Teams implementing automated intake and extraction can utilize the API reference documentation, dashboard user guides, and direct support resources. These documentation tools help technical teams connect interaction data and extraction outputs directly into their internal systems and workflows.