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💰 Sales🏗️ 4 Tech Levels🚀 Production-Grade

Sales Enablement AI

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

June 13, 2025
demointeractivesales-enablementsalesmulti-agent
🤖Demo 1 of 4

Advanced Multi-Agent System

BOFU: Production LangGraph with Router → Specialized Agents → Aggregation

1. Select Analysis Scenario

Query requiring multiple specialist agents: 'Should we prioritize this $500K enterprise deal? What's our win probability and what training does the team need?'
Competitors: Enterprise Deal: Acme Corp ($500K ARR), Team Capability: Current vs Required Skills, Pipeline Context: Q2 Revenue Target $2.3M

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 → Executes get_deal_data() → Returns result

Monitoring:Acme Corp
ai-agent-terminal

Terminal ready. Run simulation to begin.

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🔍Demo 3 of 4

RAG-Based Search

MOFU: Search 100+ documents with vector similarity

Search Query

"Find Objection Handler"

Embed query → Search vectors → Retrieve objection handler chunks → Generate customized response

Document Sources:Sales Playbook: Pricing Objections (page 23)Case Study: Enterprise Deal - Price JustificationTraining Doc: Value-Based Selling FrameworkObjection Handler Library: Cost vs ROI

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: salesforce_ingestion(50 deals) → deal_scorer(ML model) + email_enricher(Clearbit) in parallel → pipeline_forecaster(revenue model) → alert_router(high-risk deals)

Integrations:Salesforce: 52 active dealsClearbit: 89 contacts enrichedML Model: 52 deals scoredPipeline Forecast: $2.3M → $2.1M (2 deals at risk)Alerts: 3 high-risk deals, 1 training gap
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 Sales Enablement System?

We'll build your custom system: MCP tools (TOFU) → RAG search (MOFU) → Multi-tool (MOFU) → Multi-agent (BOFU). From demos to deployment in 8 weeks.

Book Architecture ReviewStart with MCP Tools (TOFU)
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