How to Use big4.cloud

Practical examples, best practices, and workflows for getting the most out of the strategic analysis engine.

🚀 Quick Start (2 minutes)

After installing the skill and configuring the MCP server, simply ask your AI assistant a strategic question:

"Analyze whether we should enter the German market for our B2B SaaS product"
The engine automatically triggers, asks context questions, and delivers a structured consulting-grade analysis in ~6-12 minutes.
💡 Tip: The more context you provide upfront, the better the analysis. Include revenue, team size, current markets, and specific concerns.

📊 Analysis Types

Market Sizing (TAM/SAM/SOM)

"Market sizing for AI-powered compliance tools in European banking. We're a 5-person team with a working MVP, €200K ARR, targeting mid-size banks (€1-50B AUM)."

Competitive Landscape

"Competitive analysis: our project management tool vs Asana, Monday.com, and ClickUp. We differentiate on AI automation. $50/user/month pricing."

Due Diligence

"Due diligence on acquiring TechStartup Inc: €3M revenue, 20 employees, asking €15M. They do AI customer service. We're a CRM company with 500 enterprise clients."

Investment Thesis

"Evaluate this investment: pre-revenue AI company asking €5M for 20%. Claims proprietary technology, solo founder, no patents."

Strategic Planning

"We need to pivot from B2C marketplace (€50K MRR, declining 10% monthly) to B2B SaaS. 8 engineers, 3 salespeople, 18 months runway. Options and plan?"

🎯 Advanced Features

Curator Panel (Multi-Model) 5 credits

For important decisions, use the panel mode — three different AI models analyze from strategic, critical, and operational perspectives:

"Analyze [topic] with curator_mode: panel"
Three models (DeepSeek, Gemini, Qwen) produce independent sections, then an Assembler merges without repetition. Deeper, more comprehensive output.

Audience Simulation 5 credits

Test how your target audience would react BEFORE presenting:

"Simulate how Series B investors would react to this pitch" (after getting a deliverable)
8 AI personas (risk-averse CFO, aggressive growth investor, skeptical technical due-diligence lead...) read your recommendation and give honest reactions. Sentiment score tells you if you're ready.

Deep Audit 15 credits

The most comprehensive validation available — 10 phases that transform any analysis into investment-grade:

"Audit this analysis" (after decision_result)
What you get:
✓ Fact-check against real data (Polymarket, Reddit, web)
✓ Audience simulation (all stakeholders react)
✓ Enhanced deliverable (fixed contradictions, grounded claims)
✓ Confidence Delta: "Confidence: 35% → 62% (+27 pts)"
✓ Kill Criteria: "Abandon if X happens within 30 days"
✓ Contradiction Map: where sources disagree
✓ Time-Travel: "3 months ago this would have been different because..."
✓ Drift Monitor: tracks your assumptions over time
⚠️ Best for: Pitch decks before investor meetings, board presentations, M&A decisions, market entry strategies. Not needed for quick operational questions.

💡 Best Practices

1. Always provide context

The engine asks questions if you don't provide context. But you'll get faster, better results by including:

2. Attach documents

Upload PDFs, pitch decks, financial reports. They get converted to Markdown and used as grounded context. The analysis will reference YOUR data, not generic assumptions.

3. Use the right tier

Question TypeRecommended TierTime
"Should I do X or Y?"Fast~6 min
Market entry, partnership evalNormal~12 min
M&A, major investment, pivotDeep~45 min
Investor pitch, board presentationNormal + Deep Audit~25 min

4. Run the Deep Audit on anything that goes to stakeholders

If the analysis will be seen by investors, a board, or clients — run the Deep Audit. The confidence delta and kill criteria make the difference between "AI-generated" and "consulting-grade".

5. Build a knowledge base

Upload your company docs, market research, competitive intel. The engine searches your knowledge base in every analysis. Over time, it becomes smarter about YOUR specific context.

📋 Workflow Examples

Investor Pitch Preparation

  1. Upload your pitch deck → convert_document
  2. Run: "Evaluate our investment thesis and valuation" → decision_start (normal)
  3. Run: Deep Audit on the result → decision_audit_deep
  4. Simulate investor reactions → simulate_audience
  5. Fix the pitch based on objections
  6. Re-run with the fixed version → verify confidence improved

M&A Due Diligence

  1. Upload target company financials + market data
  2. "Due diligence on acquiring [target] for [price]" → deep tier
  3. Deep Audit → fact-checks the target's claims against public data
  4. Audience Simulation with "board of directors, CFO, legal counsel"
  5. Review kill criteria: "walk away if..."

Weekly Strategic Review

  1. "Analyze our competitive position this week" → fast tier (saves credits)
  2. The drift monitor alerts if market conditions changed since last analysis
  3. Re-run full analysis only if drift detected

💰 Credits Guide

ActionCreditsWhat you get
Quick analysis (fast)1Structured report, ~6 min
Full analysis (normal)1Complete pipeline + adversarial, ~12 min
Deep analysis3Exhaustive 5-round + assumption audit, ~45 min
Curator Panel (multi-model)53 AI models + assembler
Audience Simulation58 personas react to your strategy
Deep Audit1510-phase validation: fact-check + audience + enhancement + kill criteria + time-travel
Check credits / documents / memory0Always free