•Implemented a Supervisor Agent with a multi-agent architecture using LangChain,
enabling efficient coordination and task delegation among AI agents for faster and
more reliable automation.
•Developed a real-time transcription and diarization system, delivering fast,
speaker-separated transcripts that enhanced summarization quality.
•Optimized LangChain’s memory performance by building a custom Supabase
memory saver, reducing storage overhead and improving retrieval speed across
agent interactions.
•Cut LLM extraction latency by over 55%, reducing response time from 23 seconds to
10 seconds by optimizing the Extraction Agent’s design and flow, resulting in a
much smoother user experience.
•Resolved Airbyte localhost API issues, enabling smoother local development and
significantly reducing debugging time during data migration workflows.
•Built a full-stack, AI-integrated chat system with WebSocket-based real-time
messaging, providing instant, responsive interaction between users and AI agents.
