FLAGSHIP CASE STUDY
PHHM Multi-Agent AI Platform
A modular Generative AI platform built around six specialised agents collaborating through a central orchestration layer — cutting workflow time by 85% and errors by 73%.
6
Specialised AI agents
85%
Faster workflows
73%
Fewer errors
100%
Configuration-driven
The Problem
Complex organisational workflows spanning member communication, care coordination, analysis and content generation were being handled through disconnected manual processes, leading to slow turnaround times and inconsistent outputs across teams.
The Solution
I architected a six-agent Generative AI ecosystem where each agent specialises in one domain, coordinated through a central orchestration layer that manages task delegation, parallel execution and output validation — replacing manual handoffs with an automated, auditable pipeline.
Six Specialised Agents
Overseer, Welcome, Analyst, Care, Communications and Gospel agents each handle a distinct domain of the workflow.
Central Orchestration Layer
Routes tasks between agents, manages shared state, and coordinates handoffs without manual intervention.
85% Faster Workflows
Parallelised agent execution cuts end-to-end processing time compared to sequential manual handling.
73% Fewer Errors
Schema validation and agent-level checks catch inconsistencies before they propagate downstream.
Role-Based Access
Each agent operates within defined permission boundaries, matching real organisational responsibilities.
Configuration Over Code
JSON/YAML-driven behaviour lets non-technical users adjust agent logic without touching source code.
How It Works
Task Intake
The Overseer agent receives an incoming request and determines which specialised agents need to be involved.
Agent Delegation
Tasks are routed to the Welcome, Analyst, Care, Communications or Gospel agent based on domain.
Parallel Processing
Multiple agents work concurrently where tasks are independent, cutting total processing time.
Validation Layer
Outputs are checked against schema and business rules before being passed downstream.
Orchestrated Output
The Overseer consolidates agent outputs into a single coherent result for the end user.
Outcome
The platform reduced end-to-end workflow time by 85% and cut output errors by 73%, replacing fragmented manual coordination with a single orchestrated system that scales without adding headcount.