Form Assistant AI¶
Intelligent form completion with auto-fill, validation, and real-time guidance
Important Market Disclaimer
Auto-fill suggestions and validation thresholds are based on Oklahoma City market data.
Regional differences affect:
- Rehab cost estimates (see Rehab Estimation for market adjustments)
- Holding cost calculations (property taxes, insurance rates vary by state)
- DOM benchmarks (what's "slow" in OKC may be normal elsewhere)
Always verify AI suggestions against YOUR local market conditions. These are educational starting points based on Cameron's OKC experience.
What Is Form Assistant AI?¶
Form Assistant AI goes far beyond tooltips. It actively participates in your deal analysis - suggesting values, validating inputs, flagging risks, and learning from your history.
graph TB
subgraph "Traditional Form"
T1[Empty field] --> T2[User guesses]
T2 --> T3[No validation]
T3 --> T4[Submit & hope]
end
subgraph "AI Form Assistant"
A1[Enter address] --> A2[AI auto-fills comps, ARV, market data]
A2 --> A3[AI validates: 'ARV looks 12% high']
A3 --> A4[AI suggests: 'Reduce to $152K?']
A4 --> A5[User confirms with confidence]
end
style T4 fill:#ef4444,color:#fff
style A2 fill:#3b82f6,color:#fff
style A3 fill:#f97316,color:#fff
style A4 fill:#6366f1,color:#fff
style A5 fill:#22c55e,color:#fff
Core AI Capabilities¶
1. Smart Auto-Fill¶
When you enter a property address, AI pre-populates fields:
flowchart LR
subgraph "User Input"
A[Enter: 123 Main St
Cleveland, OH 44105] end subgraph "AI Analysis" P[PropStream API] M[MLS Comps] C[County Records] R[Rental Data] end subgraph "Auto-Filled" F1["ARV: $158,000
(3 comps avg)"] F2["Rehab Est: $38,500
(based on 1955 build)"] F3["Rent: $1,450/mo
(market rate)"] F4["Holding: $6,200
(4 mo typical)"] end A --> P & M & C & R P & M & C & R --> F1 & F2 & F3 & F4 style A fill:#3b82f6,color:#fff style F1 fill:#22c55e,color:#fff style F2 fill:#22c55e,color:#fff style F3 fill:#22c55e,color:#fff style F4 fill:#22c55e,color:#fff
Cleveland, OH 44105] end subgraph "AI Analysis" P[PropStream API] M[MLS Comps] C[County Records] R[Rental Data] end subgraph "Auto-Filled" F1["ARV: $158,000
(3 comps avg)"] F2["Rehab Est: $38,500
(based on 1955 build)"] F3["Rent: $1,450/mo
(market rate)"] F4["Holding: $6,200
(4 mo typical)"] end A --> P & M & C & R P & M & C & R --> F1 & F2 & F3 & F4 style A fill:#3b82f6,color:#fff style F1 fill:#22c55e,color:#fff style F2 fill:#22c55e,color:#fff style F3 fill:#22c55e,color:#fff style F4 fill:#22c55e,color:#fff
What Gets Auto-Filled:
| Field | Data Source | Confidence |
|---|---|---|
| ARV | 3 nearest comps, adjusted | 85% |
| Rehab Estimate | Age, sqft, typical scope | 70% |
| Rent Estimate | Rentometer + local data | 80% |
| Holding Costs | Market avg DOM × carrying | 75% |
| Closing Costs | Standard % by state | 90% |
| Property Tax | County records | 95% |
💡 User Override: All auto-filled values are suggestions. Click to edit or accept.
2. Real-Time Validation¶
AI validates every field as you type, catching errors before you submit:
┌─────────────────────────────────────────────────────────────┐
│ ARV (After Repair Value) │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ $185,000 │ │
│ └─────────────────────────────────────────────────────────┘ │
│ │
│ ⚠️ AI VALIDATION WARNING │
│ ────────────────────────────────────────────────────────── │
│ Your ARV of $185,000 is 17% HIGHER than comparable sales: │
│ │
│ • 456 Oak St (0.2mi): Sold $152,000 - 3bd/2ba, 1,380 sqft │
│ • 789 Elm Ave (0.3mi): Sold $161,000 - 3bd/2ba, 1,420 sqft │
│ • 321 Pine Dr (0.4mi): Sold $158,000 - 3bd/1.5ba, 1,350 sqft│
│ │
│ 📊 Suggested ARV: $155,000 - $162,000 │
│ │
│ [Accept $158,000] [Keep $185,000] [Explain my reasoning] │
└─────────────────────────────────────────────────────────────┘
Validation Rules Applied:
| Check | Threshold | Action |
|---|---|---|
| ARV vs Comps | ±15% | ⚠️ Warning |
| Rehab vs Scope | ±25% | ⚠️ Warning |
| Profit Margin | <10% | 🔴 Red flag |
| 70% Rule | Exceeds MAO | 🔴 Red flag |
| Holding vs Timeline | Mismatch | ⚠️ Warning |
| Cash-on-Cash | <8% BRRRR | 🟡 Caution |
3. Scenario Modeling¶
See how changes impact your deal in real-time:
flowchart TB
subgraph "Current Deal"
C1["Purchase: $95,000"]
C2["ARV: $158,000"]
C3["Rehab: $38,500"]
C4["Profit: $12,500"]
end
subgraph "AI What-If Scenarios"
W1["🔻 If ARV drops 10%"]
W2["🔺 If rehab runs 20% over"]
W3["💰 If you negotiate $5K off"]
end
subgraph "Impact Analysis"
I1["Profit: $-3,300
❌ Deal becomes loss"] I2["Profit: $4,800
⚠️ Below 10% margin"] I3["Profit: $17,500
✅ Strong deal"] end C1 & C2 & C3 & C4 --> W1 & W2 & W3 W1 --> I1 W2 --> I2 W3 --> I3 style I1 fill:#ef4444,color:#fff style I2 fill:#eab308,color:#000 style I3 fill:#22c55e,color:#fff
❌ Deal becomes loss"] I2["Profit: $4,800
⚠️ Below 10% margin"] I3["Profit: $17,500
✅ Strong deal"] end C1 & C2 & C3 & C4 --> W1 & W2 & W3 W1 --> I1 W2 --> I2 W3 --> I3 style I1 fill:#ef4444,color:#fff style I2 fill:#eab308,color:#000 style I3 fill:#22c55e,color:#fff
Scenario Sliders:
| Adjust | Range | See Impact On |
|---|---|---|
| ARV | ±20% | Profit, ROI, Deal Score |
| Rehab | ±30% | Profit, cash needed |
| Timeline | 2-8 months | Holding costs, ROI |
| Purchase | ±$10K | MAO compliance, profit |
| Interest Rate | 6-14% | Holding costs, BRRRR cash flow |
4. Conversational Refinement¶
AI asks clarifying questions to improve accuracy:
sequenceDiagram
participant U as User
participant AI as Form Assistant AI
participant DB as Market Data
U->>AI: Enters $45,000 rehab estimate
AI->>U: "That's a substantial rehab. What's the scope?"
U->>AI: "Kitchen, 2 baths, flooring, paint, HVAC"
AI->>DB: Lookup Cleveland pricing
DB-->>AI: Return itemized costs
AI->>U: "Based on that scope, typical range is $42K-$55K"
AI->>U: "Your $45K is reasonable. Want me to build a detailed SOW?"
U->>AI: "Yes"
AI-->>U: Generates 47-item SOW with line pricing
Questions AI Might Ask:
| Field | Clarifying Question |
|---|---|
| Rehab | "What's your scope? Kitchen/baths/cosmetic/full gut?" |
| ARV | "Are you targeting retail buyers or investors?" |
| Timeline | "Using contractors or DIY? Full-time or weekends?" |
| Financing | "Hard money, DSCR, conventional, or cash?" |
| Exit | "Flip, BRRRR, or long-term rental?" |
5. Proactive Risk Warnings¶
AI flags deal-killers before you get too far:
🚨 AI RISK DETECTION
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⛔ CRITICAL: Single Exit Strategy
Your numbers only work for flip. If market slows:
• Rental cash flow: -$180/mo (negative)
• BRRRR refi: Would leave $28K in deal
Recommendation: Reduce purchase price by $8K to enable backup exits
⚠️ WARNING: Thin Margin
10.2% profit margin is below Cameron's 15% comfort zone
• Room for error: Only $16,000
• One surprise = break-even deal
📹 Watch: "Why I Require 15% Minimum" - Module 9 (3:47)
ℹ️ NOTE: Market Cooling
ZIP 44105 showing 8% price decline last 90 days
• DOM increased from 24 → 38 days
• Consider conservative ARV of $150K
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
6. Learning & Personalization¶
AI improves by learning from YOUR deals:
graph TB
subgraph "Your History"
H1[Deal 1: Estimated $35K rehab
Actual: $42K] H2[Deal 2: Estimated $28K rehab
Actual: $31K] H3[Deal 3: Estimated $40K rehab
Actual: $48K] end subgraph "AI Learning" L[Pattern Detection:
You underestimate by ~18%] end subgraph "Personalized Suggestion" S["Your estimate: $38,000
AI adjusted: $44,800
(+18% based on your history)"] end H1 & H2 & H3 --> L --> S style L fill:#3b82f6,color:#fff style S fill:#22c55e,color:#fff
Actual: $42K] H2[Deal 2: Estimated $28K rehab
Actual: $31K] H3[Deal 3: Estimated $40K rehab
Actual: $48K] end subgraph "AI Learning" L[Pattern Detection:
You underestimate by ~18%] end subgraph "Personalized Suggestion" S["Your estimate: $38,000
AI adjusted: $44,800
(+18% based on your history)"] end H1 & H2 & H3 --> L --> S style L fill:#3b82f6,color:#fff style S fill:#22c55e,color:#fff
Personalization Features:
| Feature | What It Learns |
|---|---|
| Rehab Accuracy | Your estimate vs actual delta |
| Timeline Accuracy | Your projected vs actual timeline |
| ARV Accuracy | Your ARV vs actual sale price |
| Preferred Markets | ZIP codes you analyze most |
| Deal Criteria | Your typical buy box parameters |
Field Intelligence Matrix¶
| Field | Auto-Fill | Validation | Scenarios | Learning |
|---|---|---|---|---|
| ARV | ✅ From comps | ✅ vs market | ✅ ±10-20% | ✅ Accuracy |
| Purchase Price | ❌ User input | ✅ vs MAO | ✅ Negotiation | ❌ |
| Rehab Estimate | ✅ Age/scope | ✅ vs typical | ✅ ±30% | ✅ Accuracy |
| Holding Costs | ✅ Calculated | ✅ vs timeline | ✅ Rate changes | ❌ |
| Closing Costs | ✅ % of price | ✅ vs typical | ❌ | ❌ |
| Rent Estimate | ✅ Market data | ✅ vs comps | ✅ Vacancy | ✅ Accuracy |
| Cap Rate | ✅ Calculated | ✅ vs market | ✅ Expense adj | ❌ |
Form Assistant by Tier¶
| Feature | Free | Solo | Pro | Team |
|---|---|---|---|---|
| Basic field definitions | ✅ | ✅ | ✅ | ✅ |
| Cameron's tips + video links | ❌ | ✅ | ✅ | ✅ |
| Smart auto-fill suggestions | ❌ | ❌ | ✅ | ✅ |
| Real-time validation | ❌ | ✅ | ✅ | ✅ |
| Scenario modeling | ❌ | ❌ | ✅ | ✅ |
| Conversational refinement | ❌ | ❌ | ✅ | ✅ |
| Proactive risk warnings | ❌ | ✅ | ✅ | ✅ |
| Personalized learning | ❌ | ❌ | ❌ | ✅ |
| Custom team defaults | ❌ | ❌ | ❌ | ✅ |
Technical Architecture¶
flowchart TB
subgraph "User Interface"
Form[Deal Analysis Form]
end
subgraph "Form Assistant AI Engine"
Auto[Auto-Fill Engine]
Valid[Validation Engine]
Scenario[Scenario Engine]
Learn[Learning Engine]
end
subgraph "Data Sources"
Props[PropStream API]
MLS[MLS/Comps]
Price[Pricing Database]
User[User History]
Qdrant[Cameron Content
3,268 chunks] end subgraph "AI Layer" Claude[Claude API] Embed[Embeddings] end Form --> Auto & Valid & Scenario Auto --> Props & MLS Valid --> Price & Qdrant Scenario --> Claude Learn --> User Qdrant --> Embed --> Claude style Auto fill:#3b82f6,color:#fff style Valid fill:#f97316,color:#fff style Scenario fill:#6366f1,color:#fff style Learn fill:#22c55e,color:#fff style Claude fill:#22c55e,color:#fff
3,268 chunks] end subgraph "AI Layer" Claude[Claude API] Embed[Embeddings] end Form --> Auto & Valid & Scenario Auto --> Props & MLS Valid --> Price & Qdrant Scenario --> Claude Learn --> User Qdrant --> Embed --> Claude style Auto fill:#3b82f6,color:#fff style Valid fill:#f97316,color:#fff style Scenario fill:#6366f1,color:#fff style Learn fill:#22c55e,color:#fff style Claude fill:#22c55e,color:#fff
Implementation Roadmap¶
| Phase | Capability | Complexity |
|---|---|---|
| Phase 1 | Basic definitions + tips | ✅ Done |
| Phase 2 | Real-time validation | Medium |
| Phase 2 | Risk warnings | Medium |
| Phase 3 | Smart auto-fill | High |
| Phase 3 | Scenario modeling | High |
| Phase 4 | Conversational refinement | Very High |
| Future | Personalized learning | Very High |
Comparison: Basic Help vs AI Form Assistant¶
| Aspect | Basic Help (Tooltips) | AI Form Assistant |
|---|---|---|
| Input Method | User types everything | AI suggests, user confirms |
| Validation | None until submit | Real-time as you type |
| Data Sources | Static definitions | Live market data |
| Personalization | None | Learns from your history |
| Risk Detection | Manual review | Proactive warnings |
| Accuracy | Depends on user skill | AI-augmented estimates |
| Time to Complete | 15-20 minutes | 3-5 minutes |
Form Assistant AI transforms data entry into intelligent collaboration
See Deal Review AI for automated deal scoring
See Ask Cameron for natural language Q&A