Multi-Agent Intelligence

Multi-Agent AI Architecture

Experience the power of multiple specialized AI agents working collaboratively to deliver comprehensive, robust data analysis that's impossible with single-agent systems.

How Multiple AI Agents Transform Analysis

Unlike traditional single-agent systems, AFASAsk deploys 3-5 specialized AI agents working simultaneously, each bringing unique analytical perspectives and methodologies to ensure comprehensive, validated results.

Collaborative Intelligence

Multiple agents work together, sharing insights and validating each other's findings

Dynamic Adaptation

Configurable analysis depth from 3-22 steps based on query complexity

Quality Assurance

Built-in error recovery and cross-validation between agents

Agent Workflow Visualization

A1
Schema Explorer Agent
Analyzes database structure and relationships
A2
Query Optimization Agent
Generates efficient PySpark queries
A3
Insight Generation Agent
Interprets results and creates narratives

Advanced Agent Capabilities

Each agent brings specialized skills and operates with sophisticated AI models to deliver enterprise-grade analysis

Persistent Memory

Agents maintain context across conversation sessions with advanced fact notation systems.

✓ Learns from every interaction

Code Generation

Generates and executes PySpark code for enterprise-scale data processing.

✓ Handles multi-table analyses

Error Recovery

Sophisticated error handling with automatic correction and learning capabilities.

✓ Self-improving system

Real-Time Progress

Live visibility into each agent's analytical process with WebSocket streaming.

✓ Watch analysis unfold live

Best-Answer Selection

Advanced synthesis algorithms identify optimal insights from multiple perspectives.

✓ Quality through competition

Model Flexibility

Works with any AI model - GPT-4, Claude, Llama, or custom enterprise models.

✓ Model-agnostic architecture

Technical Implementation

Built on modern, scalable architecture optimized for multi-agent coordination and enterprise performance

Agent Orchestration

LangChain/Autogen framework
WebSocket real-time communication
Asynchronous processing pipeline
Intelligent load balancing

Performance Metrics

Concurrent Agents 3-5 simultaneous
Analysis Steps 3-22 configurable
Response Time <5 seconds
Memory Retention Persistent

Experience Multi-Agent Intelligence

See how multiple AI agents working together deliver insights impossible with single-agent systems