AI QA Document Search Agent

How Cassidy automates quality and audit systems using AI

Step 1: Connect quality and audit systems

Cassidy syncs with your QMS, document management systems, engagement repositories, and knowledge portals—ingesting policies, SOPs, EQR checklists, RCA logs, and methodology templates while preserving source-native access controls.

Step 2: Map permissions and identities

Cassidy integrates with your identity provider to enforce RBAC at retrieval time, applying engagement-based ACLs, functional role restrictions, and jurisdictional ring-fencing so users only access entitled content.

Step 3: Normalize and enrich audit content

Documents are processed with OCR for scanned workpapers, chunked for optimal retrieval, and enriched with metadata—engagement codes, applicable standards (ISA/PCAOB AS/ISQM), deficiency types, effective dates, and version tracking.

Step 4: Retrieve with hybrid search and policy filters

When a QA manager queries the Agent, Cassidy expands audit acronyms (EQR, EQCR, KAMs, RCA), runs hybrid retrieval across permission-filtered indices, and reranks results to prioritize current-effective, jurisdiction-appropriate content.

Step 5: Generate grounded responses with citations

Cassidy composes answers strictly from retrieved passages, providing inline citations with document titles, effective dates, and deep links to immutable versions—supporting evidence traceability for cold file reviews and ISQM 1 compliance.

Step 6: Deliver and log for audit trail

Responses are delivered with an evidence view for quick verification, while retrieval candidates, filters applied, and final citations are logged to support quality monitoring, RCA on failures, and corrective action workflows.