Back to Products Apra Labs

Multi-Agent Conversational AI

Supervisor-pattern agent orchestration

Designed and built a multi-agent conversational system using a supervisor pattern that routes user queries to 5 specialized agents: Reporting, Admin, System Setup, Knowledge, and Support Tickets. Each agent has its own tool registry, context window management, and fallback strategies. The system handles complex multi-turn conversations over a 4 TB database with real-time streaming responses via SignalR.

5

specialized agents

4 TB

database queried

Real-time

streaming via SignalR

300+

facilities served

Architecture & Implementation

How it's built

01

Supervisor agent with intent classification and routing logic

02

Registry-driven tool system — each agent declares its capabilities

03

Two-tier RAG: graph-based retrieval + dense vector search

04

Multi-turn conversation management with context windowing

05

SignalR integration for real-time streaming responses

06

Fallback chains when primary agent cannot resolve