IC ROOT // COCKPIT
#QNS-EXEC-ECONOMICS-BLEED-READY
💰

Unit Economics & Cash Burn

// Runway & Margins

Why you're here: Top-line revenue looks active, but cash is quietly evaporating. SaaS licenses are unmanaged, gross margins are compressed, and customer acquisition costs exceed lifetime value.

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Founder / CTO Lens: Direct technical & operational diagnostic active. Select symptoms below to isolate bottlenecks.
Cash Runway Remaining (Months until zero cash) 9 – 12 Months
> 18m12m6m< 90d
Monthly Net Burn / Drain (Net cash deficit/mo) $20k – $50k / mo
< $10k$20k–$50k$60k–$120k> $150k
Observed Friction Points (Tap all that apply) 0 Selected
Rough estimates are 100% fine
🎯 Target Outcome Mandate (What does victory look like on Monday?)
Select desired remediation
🎙️

Hands-Free Friction Dump // Minimize Typing

Web Speech API Dictation Ready

IC Root // Briefing Vault & Asynchronous Settlement

Sandboxed
✓ Saskatchewan MNDA & Zero AI Training Law
Select Diagnostic Service Tier (Stripe CAD Settlement) 100% Tax Deductible Business Expense
Targeted Triage $350 CAD
48h SLA
Scope: Single Bottleneck

Strictly isolated to 1 acute bottleneck, API loop, pricing leak, or critical bug audit. Tactical remediation without cross-domain synthesis.

RECOMMENDED
Teardown Memo $850 CAD
5-Day SLA
Scope: Cross-Domain Synthesis

Full cross-domain synthesis: correlates how friction across multiple modules (unit economics, architecture, velocity) interconnects, with a 14-day patch plan.

Full Deep Dive $2,250 CAD
Priority SLA
Scope: Forensic & Governance

End-to-end forensic audit: raw code profiling, vendor/contract IP review, refactor specifications, and executive board memo.

📁 Click to upload or drag files here PDF, PNG, JPG, JSON, LOG, TXT, CSV (Max 25MB)
🛡️ MNDA GUARANTEE & STATUTORY ZERO-AI WARRANTY #ICROOT-SHA256-VERIFIED

Submitting materials under the IC Root Diagnostic Protocol initiates binding mutual non-disclosure under Saskatchewan law. EXPLICIT WARRANTY: Zero client code, financials, schematics, or briefing context are ever retained or utilized to train, fine-tune, or adapt any public or third-party AI foundation models.

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