Multi-Agent Communication Orchestrator
Deploys an 8-agent AI system that orchestrates the entire communication lifecycle: retrieves relevant templates and regulations via RAG, generates personalized content with cultural adaptation, translates to multiple languages, predicts engagement outcomes, optimizes delivery timing, and ensures complianceāall with human-in-the-loop approval workflows..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Configure AI Communication Workflow - Project selection, communication types, target resident groups, and upcoming disruptions panel
Multi-Agent Orchestration - AI agents processing with RAG knowledge retrieval showing template and regulation matches
Human-in-the-Loop Review - Multilingual content preview with quality metrics, compliance checks, and AI generation details
Communications Generated Successfully - Multi-language translations with delivery summary for email, SMS, app push, and portal
AI Agents
Specialized autonomous agents working in coordination
Master Orchestrator
Complex multi-agent workflows require centralized coordination to ensure proper sequencing, quality control, and error handling across diverse AI agents with different capabilities.
Core Logic
Coordinates all agents using chain-of-thought reasoning, manages workflow execution sequencing, delegates tasks based on agent capabilities, monitors progress across phases, handles error recovery, and ensures quality output through systematic validation. Determines parallel vs. sequential execution paths and manages inter-agent data dependencies.
Predictive Intelligence Agent
Without predictive insights, communication campaigns rely on guesswork for timing, channel selection, and content toneāresulting in lower engagement rates and resident dissatisfaction.
Core Logic
Analyzes 1,247+ historical communications to forecast resident sentiment (84% accuracy), predict response rates (72% expected), assess engagement patterns by demographic, and identify optimal timing windows. Uses ML models to generate risk scores and provides data-driven recommendations for communication strategy optimization.
Smart Scheduler Agent
Determining the optimal time and channel for communications requires analyzing multiple factorsāresident availability, construction schedules, weather conditions, and historical engagement patternsāwhich is impractical to do manually.
Core Logic
Queries external APIs (weather, construction schedule, calendar) to determine optimal delivery windows. Analyzes historical engagement data to recommend Tuesday 9:30 AM as optimal timing. Develops multi-channel strategies prioritizing SMS (94% open rate) for elderly residents and email (68% open rate) for general communications.
Risk Sentinel Agent
AI workflows can fail due to API timeouts, translation errors, or compliance violations. Without autonomous monitoring, these issues require manual intervention and delay communications.
Core Logic
Continuously monitors API latency (<5s threshold), translation confidence (>90%), compliance rule adherence (4/4 required), and cost budget ($0.15 limit). Implements self-healing protocols with automatic retry, fallback endpoint switching, and escalation handling. Provides autonomous approval confidence scoring (94%) for low-risk communications.
Knowledge Retriever Agent (RAG)
Generating accurate, compliant communications requires access to approved templates, Danish housing regulations, historical best practices, and current project documentationāinformation scattered across multiple knowledge bases.
Core Logic
Performs semantic search across 4 knowledge bases (1,406 total documents): Communication Templates (47 docs), Danish Housing Regulations (23 docs), Historical Communications (1,247 docs), and Project Documentation (89 docs). Retrieves top 5 chunks with relevance scores >0.85, returning results in 234ms with source citations for transparency.
Content Generator Agent
Creating personalized, empathetic communications for 325+ residents across 4 buildings with different concerns, languages, and communication preferences is prohibitively time-consuming when done manually.
Core Logic
Uses Claude 3 Sonnet to generate context-aware content by merging approved templates with project-specific details. Incorporates disruption information (water outage March 15), mitigation measures, and contact information. Self-validates for tone (empathetic score 0.82), readability (Grade 8), and completeness (342 words). Outputs structured content ready for translation.
Translation Specialist Agent
Diverse resident populations require communications in multiple languages (Danish, English, Arabic, Turkish, Polish, Somali). Simple translation fails to preserve cultural context, formal registers, and idiomatic expressions.
Core Logic
Translates content to 3-8 languages with cultural adaptation enabled. Handles idioms, adjusts greeting formats for Arabic cultural norms, maintains formal register for Turkish communications, and applies right-to-left formatting where needed. Achieves 96-98% translation confidence with documented cultural adaptations.
Quality Reviewer Agent
Communications must meet Danish housing law requirements (48-hour notice for utility disruptions, 14-day notice for major renovations), maintain appropriate tone, and provide accessible languageāverification that requires specialized knowledge.
Core Logic
Runs sentiment analysis (positive/empathetic score 0.84), readability assessment (Grade 8 - accessible), and compliance verification against Danish tenant notification requirements. Checks 4 mandatory rules: 48-hour notice, alternative arrangements specified, contact information provided, and accessible language level. Provides approval recommendation with improvement suggestions.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
7 technologies
Architecture Diagram
System flow visualization