The Complete DealForge AI Knowledge Base

DealForge AI is an agentic deal intelligence platform that automatically scrapes business-for-sale and CRE listings, enriches incomplete data using Census and industry benchmarks, runs full SBA financing calculations, scores every deal 0–100, and notifies matched investors via SMS — all in under 60 seconds.

The core problem: most business-for-sale listings are incomplete. An estimated 60–70% are missing cash flow, SDE, or other key financial data. Every competitor either skips these listings or forces the user to do manual research. DealForge fills the gaps automatically using a layered intelligence approach, turning "incomplete listing" into "estimated deal with confidence range."

How It Works

This is a Karpathy-pattern knowledge base: raw data is collected, then compiled by an LLM into structured articles. The system uses a multi-agent architecture where specialized agents handle discovery, parsing, enrichment, scoring, matching, and notification. The wiki is the source of truth for knowledge; the database is for fast queries.

Market Opportunity

• SBA 7(a) lending hit a record $45B across ~85,000 loans in FY2025, with acquisition-specific volume up ~35% YTD
• 80%+ of sub-$5M buyers use SBA financing — if a deal doesn't work under SBA terms, it doesn't work for most buyers
• 9,500+ completed transactions in the BizBuySell dataset form the foundation of industry benchmarks
• Median sale price rising from $337,750 overall to $375,000 in Q4 2025
• Search fund / ETA community growing rapidly — more first-time acquirers entering the market than ever

The DealForge Score answers one question: "Is this deal worth my time?" It combines seven sub-scores into a single number that accounts for both financial fundamentals and data reliability. A deal scored 85 with HIGH confidence is fundamentally different from 85 with LOW confidence — both numbers are always shown together.

Composite Formula

DealForge Score = (
    DSCR_Score        * 0.25 +    # Can it service debt?
    Multiple_Delta    * 0.20 +    # Is it priced fairly vs industry?
    Margin_Delta      * 0.15 +    # Is it profitable vs industry?
    Payback_Score     * 0.10 +    # How fast do you recover equity?
    Cash_After_Debt   * 0.10 +    # Real take-home after loan
    Industry_Risk     * 0.10 +    # Sector default rate / stability
    Data_Confidence   * 0.10      # How much do we trust the numbers?
) * 100

Sub-Score Definitions

DSCR Score (25% Weight) — Most Important

Multiple Delta Score (20% Weight)

Compares the asking price (as a multiple of cash flow) against the industry average. A deal priced 20%+ below average scores 1.0 (great deal). At average = 0.7 (fair). 30% above = 0.3 (overpriced). 60%+ above = 0.0 (avoid).

Margin Delta Score (15% Weight)

Is the business more or less profitable than its industry peers? 20%+ above average SDE margin = 1.0. At average = 0.6. 50%+ below = 0.0 (red flag).

Payback Score (10% Weight)

Cash After Debt (10%), Industry Risk (10%), Data Confidence (10%)

Cash After Debt: Absolute dollar take-home after debt service. Ranges from 0.0 ($0 or negative) to 1.0 ($300k+/yr). Industry Risk: Based on SBA default rate data — <2% default = 1.0, >6% = 0.1. Data Confidence: How much is based on reported data vs. estimates (see Section 05).

Score Interpretation

The SBA 7(a) loan program is the #1 way small businesses change hands in the United States. DealForge assumes SBA financing as the default because it's what 80%+ of sub-$5M buyers use. If a deal doesn't work under SBA terms, it doesn't work for most buyers.

Standard SBA 7(a) Terms (DealForge Defaults)

SBA Guaranty Fee Schedule

DSCR — The Key Metric

DSCR = Annual Cash Flow (SDE) / Annual Debt Service

Full Calculation Chain

1. Total Acquisition Cost = Asking_Price + Closing_Costs + SBA_Guaranty_Fee
2. Cash Down = Total_Acquisition_Cost * 0.10
3. Loan Amount = Total_Acquisition_Cost - Cash_Down
4. Monthly Payment = Loan * [r(1+r)^n] / [(1+r)^n - 1]
5. Annual Debt Service = Monthly_Payment * 12
6. DSCR = Cash_Flow / Annual_Debt_Service
7. Cash Flow After Debt = Cash_Flow - Annual_Debt_Service
8. Payback Period = Cash_Down / Cash_Flow_After_Debt

Worked Example: Auto Repair Shop ($2.1M Asking)

Most business listings are incomplete. An estimated 60–70% are missing cash flow, SDE, or other key financial data. DealForge's 4-tier enrichment framework is the primary differentiator — it fills gaps automatically using a layered intelligence approach.

The 4-Tier Classification

Enrichment Chain Paths

Path A: Employee Count Known (Most Common)

1. Source: LinkedIn, Data Axle, Google Business Profile, listing text
2. Revenue = Employees x Revenue_Per_Employee[NAICS]
3. SDE = Revenue x SDE_Margin%[NAICS]
4. Apply BEA regional price parity adjustment

Path B: Physical Units Known

Path C: Square Footage Known

Revenue/SqFt benchmarks: Grocery ($400–$600), QSR ($400–$700), Full service restaurant ($200–$400), Retail ($200–$400), Medical office ($300–$500), Gym/fitness ($30–$50/yr), Self-storage ($8–$15/yr).

Path D: Only Industry + Location Known (Lowest Confidence)

1. Query Census CBP at county level for NAICS code
2. Get average payroll per establishment
3. Revenue = Avg_Payroll / Payroll_to_Revenue_Ratio[NAICS]
4. SDE = Revenue x SDE_Margin%[NAICS]
5. Value = SDE x SDE_Multiple[NAICS]
6. Present as WIDE range with LOW confidence

Worked Example: HVAC Business, Grapevine TX

Every deal analysis is only as good as its inputs. The Data Confidence score makes uncertainty explicit. Rule: The DealForge Score and Data Confidence are ALWAYS shown together.

Confidence Levels

Confidence Point System

Total possible: 100 points. Confidence level = sum of available points / 100.

Validation Adjustments

Confidence can be reduced if data fails validation: impossible margin (-10), multiple far outside industry range (-10), Census contradicts stated employees (-15), conflicting signals (-10 each). Confidence can be increased if multiple estimation paths agree within 15% (+10) or Census data supports stated numbers (+10).

DealForge uses three valuation approaches depending on asset type and data availability: Income Approach (SDE multiples), Per-Unit/Physical Attribute Approach, and Market Comparison.

1. Income Approach (SDE Multiple Method)

The dominant method for small businesses under $5M. Business Value = SDE x SDE_Multiple[industry]

Overall average across 9,500+ transactions: 2.57x SDE / 0.67x Revenue

2. Per-Unit / Physical Attribute Approach

SDE Margin Benchmarks

The Interest Window is an investor's personalized definition of "a deal worth my time." It's a multi-dimensional preference profile where each criterion can be marked strict (must match exactly) or flexible (prefer this, but consider near-misses).

Profile Structure

Each window contains: industries (include/exclude), geography (radius or state), investment size (min/max), min DSCR, max CF multiple, min CF after debt, max payback months, min DealForge score. Each field has a flexibility toggle: strict or flexible.

How Matching Works

Notification Types

Deals move through a defined set of states from discovery to resolution. Lifecycle events like price drops and stale listings trigger re-scoring and investor notifications.

State Diagram

NEW  →  ACTIVE  →  PRICE_CHANGED  →  STALE  →  REMOVED
              ↑         │
              └─────────┘ (cycles back to ACTIVE after price change)

Deduplication Strategy

Same business can appear on multiple platforms (BizBuySell + BizQuest + BusinessesForSale). Match on: exact business name + ZIP, industry + asking price + ZIP (fuzzy), or broker name + description similarity (LLM-assisted). On match: merge into single record, keep best data from each source, note "Found on 3 platforms" as a signal of serious listing.

The end-to-end flow from deal discovery to investor SMS notification. Event-driven architecture triggered by platform email alerts, sitemap changes, and user uploads. Target: under 1 minute from trigger to SMS.

Full Pipeline Flow

Processing Time Targets

The master lookup table powering DealForge's enrichment engine, scoring, and valuation. Source: BizBuySell transaction data (9,500+ deals, Q1 2021 – Q4 2025). Median sale price: $337,750 (rising to $375,000 in Q4 2025).

Service Businesses

Building & Construction

Food & Restaurants

Healthcare & Fitness

Automotive & Marine

Retail, Manufacturing, Technology & Other

Auto Repair & Service (NAICS 811111)

Strengths: Essential service, recession-resistant, skilled labor barriers, recurring maintenance revenue. Risks: Key-man risk if owner is primary tech, labor shortages, gradual EV transition, environmental compliance. What makes a good acquisition: 4+ bays, diverse customer base, established employees who stay, long-term lease, modern diagnostics.

HVAC (NAICS 238220)

Key insight: HVAC is one of the most active PE roll-up sectors. Private equity firms (Wrench Group, Service Experts, Apex Service Partners) acquire platform companies then bolt on smaller shops, creating upward pressure on multiples. HVAC deals get snapped up fast — speed of notification matters more here than most industries.

Restaurants (NAICS 722511)

The single largest volume of small business transactions. Many investors explicitly exclude restaurants from their interest window. With 10–18% SDE margins, many fail the DSCR test. DealForge flags: "Restaurant deals under $200k SDE often struggle to meet SBA DSCR requirements."

Self-Storage (NAICS 531130)

Self-storage is a hybrid — both operating business and real estate asset. DealForge runs BOTH calculation methods. Minimal labor (1–2 part-time), recession-resistant, scalable, strong NOI margins (60–70%). Watch for: occupancy rate (85%+ healthy), market saturation from new construction, climate control premium (25–50%).

Tier Structure

Tier Comparison

Competitive Positioning

Beta Founder Program (First 5–10 Users)

12 months completely free service at chosen tier level. Hand-selected, motivated acquirers who provide weekly feedback and a referenceable review. Purpose: rapid product iteration + first social proof assets. Cost: $1,620–$3,240 total (negligible).

Universal Success Incentive (All Users, All Tiers)

Why This Works

• Outcome alignment — we only "pay" when users succeed
• Social proof generation — testimonials from actual closed deals are 10x more powerful than generic reviews
• Retention boost — successful closers have near-zero churn during free year
• CAC reduction — high-quality testimonials lower paid acquisition costs 30–50%
• Virality — "Closed a $1.4M deal and got a year free" is shareable

Revenue Per User

Gross Margin

Variable COGS Breakdown (Per User/Month)

LTV & Breakeven

Phase 0: Beta Launch (Weeks 1–8)

5–10 hand-picked users from direct network. Active acquirers, located in testable markets (Texas/DFW ideal). 1 year free service. Weekly feedback sessions. Goals: validate enrichment accuracy, tune scoring weights, test SMS timing, generate first testimonials.

Phase 1: Early Growth (Months 3–6)

Phase 2: The Flywheel (Months 6–12)

Growth Targets

Core Components

LLM Cost Optimization

Monthly LLM cost estimate at 1,000 deals/day: ~$2,160/month (parsing $300 + enrichment $360 + narratives $1,500).

Infrastructure Costs (MVP)

Total MVP infrastructure: $410–$1,100/month

• 🏛
  Census CBP / ZBP

  api.census.gov

  County and ZIP Code Business Patterns. Establishment counts, employment, payroll by NAICS. Foundation of the enrichment engine. Free but lagged 2–3 years. Use ZBP for hyperlocal density, CBP for actual payroll/employment at county level. Download bulk files (~100–200MB) for production.
• 💰
  BizBuySell

  bizbuysell.com

  Largest US business-for-sale marketplace (owned by CoStar Group). Primary listing source. Email alert parsing is the primary ethical ingestion method. Published transaction data (9,500+ deals) powers industry benchmarks. TOS prohibits scraping — email parsing is defensible.
• 🏠
  ATTOM Data

  attomdata.com

  Property ownership, tax, deed, mortgage data for 155M+ properties. Key for off-market signals: ownership duration, tax delinquency, out-of-state owner detection. API-based, pay per call.
• 🤖
  Apify Platform

  apify.com

  Scraping-as-a-service with multiple BizBuySell actors. Configurable concurrency, retries, proxy settings. Output as JSON via API. Cost: ~$1–26/mo base + compute. Use carefully per TOS considerations.
• 📊
  BLS & BEA

  bls.gov / bea.gov

  Employment wages, GDP by industry, regional price parities (RPP). BEA RPP is critical for geographic adjustments — SF/NYC multiply by 1.1–1.3, rural areas by 0.7–0.9. More current than Census (quarterly).
• 📱
  Twilio

  twilio.com

  SMS delivery for HOT MATCH alerts. Cost: ~$0.0079/segment outbound. Standard compliance handles opt-in/opt-out. Retry logic: 3x with backoff, fall back to email.
• 🌐
  FRED API (Federal Reserve)

  api.stlouisfed.org

  Daily prime rate (series DPRIME) for SBA interest rate calculations. Free, reliable. Current prime (~April 2026): ~7.50%, giving SBA rate ~10.25%.

Risk #1: Scraping / TOS Violations

BizBuySell, LoopNet, Crexi, and most marketplaces explicitly prohibit automated scraping. CoStar Group has successfully sued over mass data copying. Risk level: HIGH

Mitigation Strategy (Phased)

Risk #2: Investment Advice Liability

If DealForge says "this deal is strong — pursue it" and the investor loses money, there's potential liability. Mitigation: disclaimers everywhere, never use "buy this" language, show calculation methodology transparently, require user acknowledgment on signup.

Risk #3: Broker Licensing

Current model is SAFE: flat subscription fee regardless of deal outcomes. The 1-year-free incentive is a credit, not a transaction fee. Watch for: per-deal fees (need legal review), direct buyer-seller introductions (some states require license).

Risk #4: Outreach Compliance

Pre-Launch Compliance Checklist

Click items to mark them complete as you work through the compliance process.

• IP attorney consulted on scraping approachCritical
• Terms of Service written (user agreement)Required
• Privacy Policy written (CCPA-compliant)Required
• Investment disclaimer language approvedRequired
• CAN-SPAM compliance for outbound emailRequired
• Twilio SMS opt-in/opt-out flow implementedRequired
• Business broker licensing checked for target statesReview
• Data encryption at rest and in transit implementedRequired

15+ public-data signals indicating a business or property may be available for acquisition, even if not listed. Ranked by signal strength and scored using an Availability Likelihood framework.

High-Signal (Strong Motivation to Sell)

Medium-Signal (Likely Approaching Exit)

Soft Signals (Worth Monitoring)

Availability Likelihood Scoring

Implementation Priority