Predictive Donor Retention & Reactivation System
Provides an 8-module AI-powered retention platform featuring agent orchestration, autonomous workflow execution, AI-driven conversations, campaign autopilot, MLOps for model management, real-time command center, explainable AI diagnostics, and full observability. The system achieves high autonomy while maintaining human oversight for critical decisions.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Donor Analysis Input - Enter donor information to initiate AI-powered retention analysis with comprehensive donor profile and campaign configuration
AI Agentic Workflow Execution - Real-time monitoring of autonomous AI agents with execution status, agent activity stream, and live tool invocations
RAG Pipeline - Retrieval Augmented Generation system providing AI-generated answers with document retrieval, synthesis, and confidence scoring
Workflow Execution Results - Complete donor retention analysis with engagement scores, churn risk assessment, and AI-powered campaign recommendations
AI Agents
Specialized autonomous agents working in coordination
Churn Prevention Agent
Identifying donors at risk of churning requires continuous analysis of multiple behavioral signals and historical patterns that exceed human analytical capacity.
Core Logic
Runs continuous churn prediction pipelines analyzing donor engagement, communication responses, giving patterns, and behavioral signals. Identifies at-risk donors daily, calculates churn probability scores, and prioritizes intervention queues with high prediction confidence.
Intervention Designer Agent
Creating effective retention interventions requires understanding individual donor preferences, historical effectiveness data, and optimal channel selection - complexity that overwhelms manual processes.
Core Logic
Generates personalized intervention strategies by analyzing successful retention cases, cross-referencing donor communication preferences, and selecting optimal intervention types (phone calls, impact reports, event invitations). Provides confidence scores and expected impact estimates for each strategy option.
Agentic Workflow Executor
Complex retention workflows involving multiple steps, decision points, and tool integrations require sophisticated orchestration to execute reliably without constant human supervision.
Core Logic
Executes multi-step retention workflows autonomously, managing agent tasks, tool calls, LLM inferences, data fetches, and decision points. Supports scheduled, event-driven, manual, and AI-initiated triggers. Achieves high workflow success rate with automatic retry mechanisms and human-in-the-loop escalation for critical decisions.
Major Donor Stewardship Analyst
Major donors require personalized attention and timely touchpoints, but tracking engagement health and scheduling communications for hundreds of high-value donors manually is error-prone.
Core Logic
Assesses engagement health for major donor segments, identifies optimal touchpoint timing, and schedules personalized communications. Analyzes major donors with high confidence scoring, generating stewardship schedules that maintain strong relationships while respecting donor preferences.
Anomaly Detection Agent
Unusual donation patterns or engagement anomalies may indicate opportunities or problems that require immediate attention, but manual monitoring cannot detect these patterns in real-time.
Core Logic
Monitors donation and engagement streams in real-time, detecting statistical anomalies and pattern deviations. Triggers immediate investigation workflows, performs root cause analysis, and recommends appropriate responses. Detects anomalies rapidly with automated response initiation.
RAG Knowledge Synthesis Agent
Agents need access to organizational knowledge and best practices to make informed decisions, but searching through documentation manually is slow and inconsistent.
Core Logic
Implements Retrieval-Augmented Generation to fetch relevant documents from the knowledge base, synthesize comprehensive answers, and provide confidence-scored recommendations. Retrieves multiple documents with relevance scoring, synthesizes insights, and tracks token usage for cost management. Achieves high answer confidence with efficient token usage.
Autonomous Goal Decomposition Agent
High-level organizational goals like 'Maximize Q4 Donor Retention to 85%' require systematic breakdown into actionable subgoals with proper dependencies and agent assignments.
Core Logic
Decomposes strategic goals into hierarchical subgoal trees with progress tracking, agent assignments, priority scoring, and dependency management. Monitors goal completion across the organization, identifies blocked goals, and reallocates resources dynamically through coordinated subgoals.
Autonomous Decision Engine
Many retention decisions require rapid response but human review creates bottlenecks. The system needs to make autonomous decisions while maintaining appropriate oversight for high-impact choices.
Core Logic
Evaluates decision options using probability scoring, impact assessment, and confidence thresholds. Auto-approves high-confidence decisions while escalating uncertain or high-impact decisions for human review. Tracks decision outcomes for continuous learning with high autonomy and appropriate human oversight.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
4 technologies
Architecture Diagram
System flow visualization