Case Study
SupportPilot AI
An AI support assistant that unifies fragmented knowledge sources and accelerates monthly 30k-ticket workflows with cited answers and smart triage.
RAGCitationPII MaskingTicket TriageZendeskFreshdesk
Project Details
Knowledge was fragmented across Confluence, Notion, and internal docs. This slowed agent onboarding and caused inconsistent ticket responses.
SupportPilot AI introduced RAG-based retrieval, source-cited responses, automated ticket triage, and PII masking. The system integrated directly with Zendesk/Freshdesk, Slack, Confluence, and enterprise SSO.
+Kodcuk Approach
Architecture decisions were shaped around scale, reliability, and operational clarity.
Key Delivery Layers
+Retrieval and generation were constrained to verified sources with mandatory citation output.
+Triage scoring automatically suggested priority and routing for incoming tickets.
+PII masking policies redacted sensitive fields before assistant output reached agents.
Measured Outcomes
First response time: 9 hours to 2.1 hours
Agent resolution time improved by 22%
