A selection of the AI systems and backend platforms I've built over the years.
An agentic platform that analyzes customer support bundles and generates root cause reports automatically. It cut investigation time from hours down to under 2 minutes, secured behind OKTA SSO and observed end-to-end with LangFuse.
A code intelligence layer that indexes 30,000+ symbols using tree-sitter AST parsing. Search runs through a 4-stage hybrid pipeline — exact match, LLM query expansion, semantic search, and call graph traversal — to find the right code fast.
An open-source MCP server that lets engineers interact with Avi load balancer's REST API in natural language, featured at VMware Explore US 2025. It uses RAG-based self-correcting error recovery to keep automated workflows resilient.
A multi-source RAG system for product documentation, presented at VMware Explore Singapore 2023. It combines docs Q&A with live API function calling for controller introspection and training video recommendations.
A machine learning model that predicts Jenkins test-failure categories directly from log patterns, cutting manual triage time by 80%. Confident matches are auto-assigned to Jira tickets, closing the loop end to end.