Kranti Kumar

Abstract

The increasing scale of test automation and distributed systems has led to a rapid growth in log data, making manual analysis inefficient and time-intensive. This work presents an AI-driven log analyzer leveraging the Agentic Frameworks to enable intelligent and automated log analysis. The proposed solution utilizes agentic AI to parse logs, correlate errors, and perform context-aware root cause analysis using both textual and visual inputs such as execution logs and screenshots. By incorporating persistent memory, the system learns from historical failures and improves analysis accuracy over time. The framework enables automated categorization of failures, identification of recurring issues, and generation of actionable insights for faster resolution. This approach highlights the potential of agent-based AI systems in transforming raw log data into actionable intelligence for modern software validation workflows.

Biography:

About the Speaker: 

Kranti Kumar Appari is a Senior Solution Architect and Distinguished Member of Technical Staff (DMTS) at Wipro, bringing over 22 years of expertise in telecommunications, software engineering, and artificial intelligence. A Senior Member of the IEEE, he specializes in driving digital transformation through Software-Defined Networking (SDN) and advanced Agentic AI architectures.

Throughout his career, Kranti has pioneered significant advancements in VoIP and SDN, backed by patents in AI-driven VoIP enhancement and peer-reviewed scholarly work on SIP communication platforms. His technical leadership extends to the open-source community, where he developed a highly rated SIP PCAP analyzer, and to the global academic circuit, where he frequently serves as a keynote speaker and technical judge for international conferences. He remains at the forefront of the industry, bridging the gap between legacy telecommunications and future-ready AI automation.

 LinkedIn Profile: https://www.linkedin.com/in/krantikumarappari/