Reference Architecture
Enterprise Agentic AI Architecture
Multi-layered architecture for building scalable, secure, and production-ready AI agent systems
1
Presentation Layer
↓ Integration Flow
Web Portal
Mobile Apps
Chat Interfaces
Voice Assistants
API Gateway
2
Agent Orchestration Layer
↓ Integration Flow
Master Orchestrator
Workflow Engine
Task Router
Priority Manager
Context Handler
3
AI Agents Layer
↓ Integration Flow
Task Agents
Research Agents
Code Agents
Analysis Agents
Communication Agents
4
Frameworks & Tools
↓ Integration Flow
LangGraph
AutoGen
CrewAI
Semantic Kernel
OpenAI SDK
5
Data & Infrastructure
↓ Integration Flow
Vector DB
Knowledge Base
Event Bus
Model Registry
Monitoring
6
Enterprise Systems
CRM
ERP
HRIS
Data Warehouse
Legacy APIs
⟲
Request Flow
1
User Request
Web/Mobile/API
→
2
Auth & Routing
API Gateway validates
→
3
Task Decomposition
Orchestrator breaks down task
→
4
Agent Execution
Specialized agents process
→
5
Tool Calling
RAG, APIs, Enterprise systems
→
6
Response Synthesis
Aggregated result returned
◈
Technology Stack
Frameworks
LangGraph
AutoGen
CrewAI
Platforms
AWS Bedrock
Azure AI
Vertex AI
Infrastructure
Pinecone
Redis
Kafka
Observability
LangSmith
Weights & Biases
Datadog
⬡
Agent Hierarchy & Coordination
Master Controller
Orchestrator Agent
Decomposes tasks, routes to specialists, aggregates results
Planner
Router
Monitor
Specialist Workers
Task Agents
Execute specific domain tasks with focused expertise
Code Gen
Data Analysis
Content
System Integrators
Tool Agents
Interface with external APIs, databases, and services
API Caller
DB Query
File I/O
Quality Control
Validator Agents
Verify outputs, check compliance, ensure accuracy
Fact Check
Schema Validate
Safety
⛨
Enterprise Security & Governance Layer
🔐
SSO / RBAC
Identity & Access
📋
Audit Logging
Full Traceability
🛡️
Data Encryption
At Rest & Transit
⚖️
Compliance
SOC2, GDPR, HIPAA
🔒
Guardrails
Output Filtering
📊
Rate Limiting
Cost Control