The Enterprise Solution for Smarter Case Management
Automatic Case Classification
Next Best Action Prediction
Case & Knowledge Clustering
Analytics & Reporting
Built-In Multi-Agent Orchestration
Impact of Smarter Case Classification
01
Accelerates Case Resolution
Ensures every case reaches the right agent instantly through AI-powered classification, reducing delays and improving resolution times.
02
Drives Product Enhancements
Highlights recurring issues, feature requests, and product gaps using insights from case clustering, enabling faster product enhancements and better roadmap decisions.
03
Improves Customer Satisfaction
Assists in accurate and precise categorization, ensuring tickets are routed to the right agents for timely resolution, boosting CSAT and CX.
04
Boosts Knowledge Creation
Provides insights on case types, making it easier to figure out the case clusters and look for an opportunity for knowledge creation.
05
Ensures Proactive Support
Predicts the most effective resolution path, reducing escalations and ensuring customers receive timely, context-aware responses.
Industry Recognitions
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Frequently Asked Questions
Intelligent case classification uses AI and machine learning to analyze and categorize support queries based on context, intent, and content. Instead of relying on manual sorting or static rules, it assigns queries in real time to categories like billing, troubleshooting, or feature requests.
SearchUnify implements this through the AI Classification Agent, part of its Agentic AI suite, which leverages NLP, clustering, and historical case data to ensure every case is accurately identified and routed to the right resolution path.
AI Classification Agent accelerates case resolution by eliminating the need for manual triaging. When a case query comes in, the agent instantly identifies its type, whether it’s a self-service query, service request, or product issue, and routes it to the right expertise.
For example, self-service queries go to the AI Support Agent, the AI Competency Agent handles service requests, and product issues are directed to a human agent. This minimizes delays, prevents misroutes, and suggests following best actions, ensuring faster resolutions, shorter customer wait times, and improved support efficiency.
Support teams often spend valuable time manually sorting incoming tickets or correcting misrouted cases. AI Classification Agent streamlines this process by automatically categorizing each query and routing it to the right expertise.
Simple or repetitive queries are handled by the AI Support Agent, service requests are managed by the AI Competency Agent, and complex issues are escalated to a human agent. By ensuring every query reaches the right destination, the AI Classification Agent helps teams resolve cases faster, stay focused, and maintain productivity without burnout.
Traditional rule-based routing relies on static, predefined conditions such as keywords, forms, or dropdown selections. In contrast, AI-driven classification analyzes the context and intent of each incoming case using machine learning and NLP. It accurately categorizes queries, learns from historical patterns, takes next best actions, and works seamlessly across multiple AI agents. This makes routing more dynamic, precise, and scalable than traditional rule-based systems.
First-contact resolution (FCR) depends on whether a case reaches the right AI agent or human expert on the first attempt. Accurate case classification ensures queries are correctly categorized and routed directly to the best-fit resource, without unnecessary handoffs. This improves the chances of resolving issues on the very first interaction, reduces escalations, boosts CSAT scores, and builds stronger customer trust.










