Campaign Intelligence AI - Enterprise Agentic System
Deploys a **BDI (Belief-Desire-Intention) multi-agent architecture** with 8 specialized AI agents that autonomously coordinate campaigns through DAG-based workflows, inter-agent communication protocols (FIPA-ACL), and shared knowledge blackboards. Enables autonomous goal management, real-time market intelligence synthesis, and agent swarm coordination for emergent optimization strategies.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Campaign Intelligence Workflow - 8-step process overview showing data collection and analysis phases with live execution log and real-time progress metrics
Tool Execution View - Real-time anomaly detection tool activity displaying input/output data and agent collaboration monitoring
DAG Workflow Visualization - Directed acyclic graph showing Monitor, Analyzer, and Predictor agent dependencies and execution flow
Campaign Results Dashboard - Completed Q4 Holiday Shopping Campaign showing 4.9x ROI improvement, $22,500 cost savings, 16,173 new customers, and comprehensive process summary
AI Agents
Specialized autonomous agents working in coordination
Master Orchestrator Agent
Complex campaigns require **centralized coordination** across multiple AI agents, tasks, and workflows without creating bottlenecks or single points of failure.
Core Logic
Implements **workflow management and task distribution** using priority queuing, agent lifecycle management, and DAG-based orchestration. Maintains system-wide state through distributed heartbeats and coordinates parallel agent execution with dependency resolution and checkpoint-based resumability.
Strategic Planner Agent
High-level marketing objectives need **decomposition into actionable plans** with proper resource allocation and realistic timeline estimation.
Core Logic
Performs **goal decomposition and plan generation** using hierarchical task networks. Analyzes constraints, allocates resources across agent teams, generates multi-phase execution plans, and provides timeline estimates with confidence intervals based on historical performance data.
Data Analyzer Agent
Marketing data from multiple channels contains **hidden patterns and insights** that manual analysis cannot efficiently extract at scale.
Core Logic
Executes **pattern recognition and statistical testing** across campaign data using feature extraction algorithms. Identifies correlations, segments audiences, detects anomalies, and generates actionable insights with confidence scores stored in episodic memory for future reference.
Predictive Engine Agent
Marketing teams lack **forward-looking intelligence** to anticipate campaign performance, customer behavior, and market trends.
Core Logic
Provides **time series forecasting, classification, and anomaly detection** using ML models. Generates predictions for campaign KPIs, conversion probabilities, churn risk, and market opportunities with uncertainty quantification and model explainability.
Budget Optimizer Agent
Marketing budgets are often **allocated suboptimally** across channels, campaigns, and time periods, reducing overall ROI.
Core Logic
Applies **constraint optimization and multi-armed bandit algorithms** for dynamic budget allocation. Continuously reallocates spend based on real-time performance, runs automated A/B testing, and optimizes for multiple objectives including revenue, engagement, and brand metrics.
Task Executor Agent
Planned marketing actions require **reliable execution** with proper error handling, retry logic, and completion verification.
Core Logic
Handles **task execution and workflow management** with transactional guarantees. Executes assigned operations, manages external API integrations, implements retry policies with exponential backoff, and reports execution status with detailed logs for observability.
System Monitor Agent
Multi-agent systems need **continuous health monitoring** to detect degradation, failures, and performance issues before they impact campaigns.
Core Logic
Performs **health monitoring and metric collection** across all agents and infrastructure. Tracks latency, throughput, error rates, and resource utilization. Generates alerts based on configurable thresholds and provides real-time dashboards for system observability.
Output Validator Agent
AI-generated outputs need **quality assurance and compliance verification** before deployment to ensure brand safety and regulatory adherence.
Core Logic
Implements **validation pipelines and compliance checking** for all agent outputs. Verifies content against brand guidelines, regulatory requirements (GDPR, CCPA, HIPAA, SOX, PCI), and quality thresholds. Flags issues for human review when confidence is below threshold.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
5 technologies
Architecture Diagram
System flow visualization