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🚀 Growth🏗️ 4 Tech Levels🤖 Production-Grade

Affiliate & Advocacy AI

See 4 architectures solve real problems: MCP → RAG → Multi-Tool → Multi-Agent

January 30, 2026
demointeractiveaffiliate-advocacygrowthmulti-agent
🤖Demo 1 of 4

Advanced Multi-Agent System

BOFU: Production LangGraph with Router → Specialized Agents → Aggregation

1. Select Analysis Scenario

Query requiring all specialist agents: 'Analyze our top 100 advocates, segment them, design personalized programs, and show revenue attribution'
Competitors: Customer A (NPS 10, 12 referrals, $45K influenced), Customer B (NPS 9, 8 referrals, $32K influenced), Customer C (NPS 10, 15 referrals, $67K influenced)

2. Monday's Prompt

This positioning analysis prompt from Monday's insight will be processed by Tuesday's agents in Wednesday's workflow.

3. Run Multi-Agent Workflow

You'll see 5 AI agents: Data Collector → Messaging Analyzer → Position Mapper → Strategy Advisor → Insight Generator
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🔌Demo 2 of 4

MCP Tool Use Pattern

TOFU: LLM calls tools via Model Context Protocol - see real tool execution

Automation Task

User query → LLM decides tool (identify_advocates) → Executes with criteria (NPS 9+, referrals 5+) → Returns top 10 → LLM formats answer

Monitoring:Sarah Chen (NPS 10, 12 referrals, $45K influenced)
ai-agent-terminal

Terminal ready. Run simulation to begin.

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🔍Demo 3 of 4

RAG-Based Search

MOFU: Search 100+ advocate profiles with vector similarity

Search Query

"Find Similar Advocates: 'Who are advocates similar to Marcus Johnson?'"

Embed query ('similar to Marcus Johnson') → Search vectors (10,000 profiles) → Retrieve top 5 chunks (profiles with cosine similarity > 0.85) → Generate answer (commonalities, program recommendations)

Document Sources:Marcus Johnson (Champion, 15 referrals, $67K influenced, 94 influence score)Sarah Chen (Champion, 12 referrals, $45K influenced, 89 influence score)David Park (Champion, 14 referrals, $52K influenced, 91 influence score)Lisa Wang (Champion, 11 referrals, $48K influenced, 88 influence score)James Miller (Evangelist, 9 referrals, $38K influenced, 84 influence score)

RAG Vector Search Network

Embedding
Searching
Generating
Query
Vector
Documents
Result

Search Results

Run visualization to see results

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🛠️Demo 4 of 4

Multi-Tool Orchestration

MOFU: Multiple tools working together automatically

ROI Analysis

Orchestrator calls (6am daily): Monitor Tool (scans 10,000 customers) → Identifier Tool (finds 12 new advocates) → Segmentation Tool (assigns tiers: 4 Champions, 5 Evangelists, 3 Contributors) → Attribution Tool (calculates $47K influenced revenue) → Alert Tool (Slack, Email, Dashboard)

Integrations:10,000 customers monitored (100% coverage vs 5% manual)12 new advocates identified (4 Champions, 5 Evangelists, 3 Contributors)$47,000 new influenced revenue attributed5 stakeholders alerted (Partnership team Slack, VP Growth Email, CEO Dashboard)All tools executed in parallel (8.3s total vs 8 hours manual)
Manual Process

Time to Complete

240 min

Cost per Analysis

$850

Data Points Analyzed

150

Accuracy Rate

73.0%

Reports per Day

2

Error Rate

18.0%

Ready for Production Affiliate & Advocacy System?

We'll build your custom system: MCP tools (TOFU - try tool calling) → RAG search (MOFU - search 10,000 profiles) → Multi-tool (MOFU - daily automation) → Multi-agent (BOFU - 24/7 autonomous). From demos to deployment in 8 weeks. Scale from 500 advocates manually to 10,000+ autonomously.

Book Architecture ReviewStart with MCP Tools (TOFU)
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