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July 2, 2025 26 mins

Kui Jia, Sumo Logic's Vice President of Engineering and Head of AI, shares how their AWS-powered AI agents transform chaotic security investigations into streamlined workflows.

Topics Include:

  • Kui Jia leads AI Engineering at Sumo Logic
  • SREs and SOC analysts work under chaotic, high-pressure conditions
  • Teams constantly switch between different vendor tools and platforms
  • Investigation requires quick hypothesis formation and complex query writing
  • Sumo Logic processes petabytes of data daily across enterprises
  • Company serves 2,000+ enterprise customers for 15 years
  • Platform focuses on observability and cybersecurity use cases
  • Investigation journey: discover, diagnose, decide, act, learn phases
  • Data flows from ingestion through analytics to human insights
  • Traditional workflow relies heavily on tribal domain knowledge
  • Senior engineers create queries that juniors struggle to understand
  • War room situations demand immediate answers, not learning curves
  • Context switching between tools wastes time and creates friction
  • Multiple AI generations deployed: ML anomaly detection to GenAI
  • Agentic AI enables reasoning, planning, tools, and evaluation capabilities
  • Mo Copilot launched at AWS re:Invent as AI agent suite
  • Natural language converts high-level questions into Sumo queries
  • System provides intelligent autocomplete and multi-turn conversations
  • Insight agents summarize logs and security signals automatically
  • Knowledge integration combines foundation models with proprietary metadata
  • AI generates playbooks and remediation scripts for automated actions
  • Three-tier architecture: Infrastructure, AI Tooling, and Application layers
  • Built on AWS Bedrock with Nova models for performance
  • Focus on reusable infrastructure and AI tooling components
  • Data differentiation more important than AI model selection
  • Golden datasets and contextualized metadata are development challenges
  • Guardrails and evaluation frameworks critical for enterprise deployment
  • AI observability enables debugging and performance monitoring
  • Enterprise agents achievable within one year development timeline
  • Future vision: multiple AI agents collaborating with human investigators


Participants:


Further Links:


See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

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