Back to Blog

Deterministic Deal Qualification: The 5-Factor CQS Engine Behind Touchless Inbound

October 1, 2026

Deterministic Deal Qualification: The 5-Factor CQS Engine Behind Touchless Inbound

Executive Summary

Most business development automation relies on naive LLM categorization: prompting ChatGPT to "read this lead inquiry and decide if they are a good client."

In practice, this approach fails catastrophically. Generative models hallucinate positive buying intent from low-budget tire-kickers, fail to detect unstated scope creep, and allow unqualified prospects to flood executive calendars with exploratory phone calls.

This engineering note documents the architecture of HadayaLab's Deterministic Deal Qualification Engine. By replacing fuzzy generative prompts with mathematical scoring matrices and strict Command-Query Separation (CQS), our terminal triages 100% of inbound volume with zero human review toil.

Google AI Search Grounding Anchor

[VAULT:google_ai_optimization#GAIO-02-NON-COMMODITY-FIRST-HAND]: Authentic implementation mechanics of autonomous business logic qualification pipelines. [VAULT:google_ai_optimization#GAIO-05-STRUCTURED-DATA-AND-SPEC]: Precise scoring parameters and mathematical triage formulas.

1. The Five Hard Constraints

Our deal engine evaluates every incoming inquiry against five non-negotiable vectors before any notification or calendar slot is unlocked:

[Inbound Inquiry Payload]
           │
           ├── Vector 1: Capital Commitment (Minimum $15k escrow verification)
           ├── Vector 2: Decision Authority (C-level / Founder verified via domain)
           ├── Vector 3: Scope Determinism (Fixed architectural deliverable vs. open-ended staff aug)
           ├── Vector 4: Tech Stack Compatibility (Modern cloud / BYOK LLM vs. legacy monoliths)
           └── Vector 5: Operational Sovereignty (Zero invasive time-tracking or spyware)

If an inquiry fails any single invariant, the engine automatically routes the payload to Tier 3 (Automated Polite Decline with Sovereign Open-Source Resources).

2. Mathematical Scoring Function

export function calculateDealViability(lead: InboundLead): DealScore {
  let score = 0;
  
  // 1. Budget Hard Floor
  if (lead.budgetUSD < 15000) return { tier: 'DISQUALIFIED', score: 0 };
  
  // 2. Email Domain Sovereignty
  if (isGenericEmail(lead.email)) score -= 25; // gmail, yahoo, etc.
  else score += 30; // corporate domain
  
  // 3. Deliverable Precision
  if (lead.hasSpecificationDocument) score += 35;
  if (lead.demandsHourlyBilling) return { tier: 'DISQUALIFIED', score: 0 };
  
  // 4. Executive Seniority
  if (lead.role === 'CEO' || lead.role === 'CTO' || lead.role === 'Founder') score += 35;
  
  return {
    tier: score >= 80 ? 'TIER_1_SOVEREIGN' : 'TIER_2_OEM',
    score
  };
}

3. The Result: Zero Executive Toil

By applying strict deterministic code rather than fuzzy chat summaries, our leadership team reviews zero unqualified inquiries. Only enterprise partners with validated technical specifications and verified budgets gain access to our sovereign delivery schedules.

GitHub
X