Agentic chat
Agentic chat is a multi-agent AI system with intelligent query routing, pgvector-based retrieval and semantic caching, long-term memory, document intelligence, and tool-integrated research workflows.
Agentic chat was built as a multimodal AI workspace that can decide when to use long-term memory, retrieval, vision, or external tools instead of forcing every query through the same response path. It supports deep research, web search, YouTube analysis, URL context injection, and Google Workspace actions through LangGraph-based orchestration.
Agentic chat was built as a multimodal AI workspace that can decide when to use long-term memory, retrieval, vision, or external tools instead of forcing every query through the same response path. It supports deep research, web search, YouTube analysis, URL context injection, and Google Workspace actions through LangGraph-based orchestration.
The system pairs pgvector-backed retrieval, Cohere reranking, mem0 memory, and semantic caching with streaming chat, file ingestion, and branching conversation history. In practice, that architecture enabled grounded answers across 10+ document formats, cross-conversation context retention, and a cache layer that reduced API costs by 40%.