Audit Campaign Planning Orchestrator
Orchestrates 7 specialized AI agents through phased workflow to analyze historical audit data, optimize team-store matching based on certifications and skills, generate cost-optimized travel routes, create balanced schedules respecting all constraints, validate compliance, and produce multiple plan options with risk assessments—completing in minutes what previously took weeks..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Campaign configuration interface with audit type selection, timeline parameters, and 7-agent AI orchestration setup
Agent Execution DAG showing real-time workflow coordination with agents in various execution states
AI-generated optimization plans presenting three alternatives with cost analysis and efficiency metrics
Technical analysis view with detailed agent contributions, constraint validation, and comprehensive cost breakdown
AI Agents
Specialized autonomous agents working in coordination
Campaign Orchestrator Agent
Complex multi-phase planning workflows require careful coordination of dependent tasks, agent handoffs, and checkpoint management that is difficult to manage manually across distributed systems.
Core Logic
Coordinates the entire planning workflow through phased execution. Manages task dependencies between agents, handles agent handoffs with context preservation, broadcasts status updates, resolves conflicts, and ensures all planning phases complete successfully with validated outputs.
Data Analyst Agent
Planning decisions require analysis of historical audit performance, team productivity patterns, store complexity factors, and constraint identification—data that exists across multiple systems.
Core Logic
Queries historical audit data to identify performance patterns, average durations by store type, and team productivity metrics. Analyzes constraints from client requirements, blackout dates, certification needs, and budget limitations. Builds predictive models for audit duration estimation with confidence intervals.
Resource Optimizer Agent
Matching teams to stores based on certifications (pharmacy, DEA), skill levels, and workload balance is a complex constraint satisfaction problem that humans solve suboptimally.
Core Logic
Optimizes team-store assignments considering certification requirements, skill matching scores, workload balancing, home base proximity, and utilization rates. Generates assignment matrices that maximize skill-requirement alignment while maintaining fair workload distribution across all teams.
Schedule Optimizer Agent
Creating audit schedules that respect time windows, blackout dates, store operating hours, team availability, and dependency chains across dozens of stores is computationally complex.
Core Logic
Generates feasible schedules using constraint optimization algorithms. Applies hard constraints (blackout dates, certifications, hours limits) and soft constraints (preferences, efficiency goals). Minimizes schedule conflicts, respects time windows, and produces multiple schedule alternatives ranked by optimization criteria.
Travel Optimizer Agent
Travel costs represent a significant portion of audit campaign budgets. Inefficient routing, unnecessary hotel nights, and suboptimal vehicle assignments inflate costs substantially.
Core Logic
Solves vehicle routing problems to minimize total travel distance and cost. Clusters stores geographically, optimizes multi-stop routes, determines overnight requirements, estimates travel costs including fuel, hotels, and per diem. Produces detailed route plans with segment-level timing and cost breakdowns.
Risk Validator Agent
Plans may contain hidden risks from weather disruptions, resource bottlenecks, compliance gaps, or scheduling conflicts that only emerge during execution when costly to address.
Core Logic
Validates generated plans against risk factors including weather forecasts, resource bottlenecks, compliance requirements, and scheduling conflicts. Identifies risks by category with probability and impact assessments. Generates mitigation strategies and calculates risk-adjusted confidence scores for each plan.
Synthesis Agent
Decision-makers need consolidated views comparing plan alternatives with clear trade-offs, executive summaries, and actionable recommendations rather than raw optimization outputs.
Core Logic
Aggregates outputs from all planning agents into comprehensive results. Generates executive summaries highlighting key metrics, savings, and risks. Creates comparative views of plan alternatives with trade-off analysis. Produces formatted outputs suitable for stakeholder presentation and approval workflows.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
7 technologies
Architecture Diagram
System flow visualization