Employee Engagement AI
See 4 architectures solve real problems: MCP → RAG → Multi-Tool → Multi-Agent
Advanced Multi-Agent System
BOFU: Production LangGraph with Router → Specialized Agents → Aggregation
1. Select Analysis Scenario
2. Monday's Prompt
3. Run Multi-Agent Workflow
MCP Tool Use Pattern
TOFU: LLM calls HR tools via Model Context Protocol - see real tool execution
Automation Task
User asks 'What's our engineering eNPS?' → LLM evaluates tools → Decides get_enps() is needed → Executes → Returns formatted answer
Terminal ready. Run simulation to begin.
RAG-Based Search
MOFU: Search 100+ employee surveys with vector similarity
Search Query
"Search Historical Engagement Trends"
User asks 'How have remote work concerns evolved 2023-2025?' → Embed query → Search 12 quarterly surveys → Retrieve 8 relevant chunks → Generate timeline answer with citations
RAG Vector Search Network
Search Results
Run visualization to see results
Multi-Tool Orchestration
MOFU: Multiple HR tools working together automatically
ROI Analysis
Orchestrator calls at 8am daily: scraper_tool(sources=['bamboohr', 'workday', 'slack']) → analyzer_tool(metrics=['enps', 'sentiment']) → reporter_tool(formats=['pdf', 'tableau', 'slack']) → alert_tool(thresholds={'enps_drop': 5, 'sentiment_drop': 0.15})
Time to Complete
Cost per Analysis
Data Points Analyzed
Accuracy Rate
Reports per Day
Error Rate
Ready for Production Employee Engagement 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. Prevent resignations before they happen - one prevented resignation pays for the entire system.
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