DealSignal Specification

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DealSignal

Data Into Decisions.

DealSignal is an open source AI real estate investment intelligence specification for discovering, evaluating, valuing, stress-testing, and managing residential property investment opportunities. It is designed to help investors identify potential acquisitions, determine realistic market and after-repair values, estimate renovation requirements and costs, analyze profitability, evaluate market conditions, and determine whether a property represents an opportunity or a potential liability.

DealSignal uses modular architecture so that core investment intelligence remains independent from specific data providers, property platforms, financing providers, contractors, or other vendors. Optional plugins may extend the specification with additional data sources, analytical capabilities, integrations, and specialized workflows.

Purpose

DealSignal is designed to provide an AI-assisted decision framework for residential real estate investment.

The system should be capable of understanding investment criteria expressed in natural language, discovering properties that match those criteria, analyzing recently sold comparable properties, estimating current market value and after-repair value, evaluating property condition, estimating renovation costs, analyzing market direction, calculating project profitability, identifying downside risk, and recommending whether an investment should be pursued.

DealSignal is designed to support human decision-making rather than replace professional judgment, inspections, legal review, financial advice, contractor assessment, real estate professionals, or local governmental determinations.

Core Principles

Open source architecture
Modular design
Vendor-neutral architecture
Source-independent property discovery
Natural language interaction
Evidence-based analysis
Transparent calculations
Explicit uncertainty
Risk-adjusted decision-making
Human-in-the-loop governance
Auditable investment analysis
Data provenance
Configurable investment strategies
Continuous prediction evaluation
No fabricated property information
Clear separation between verified information, estimates, assumptions, and predictions
Legal and licensing compliance for external data sources

Core Modules

Natural Language Investment Criteria Module

The Natural Language Investment Criteria Module converts natural language investment requests into structured search and analysis criteria.

The module should support:

Geographic areas
Search radius
Price ranges
Bedrooms
Bathrooms
Square footage
Lot size
Property type
Year built
Listing status
Days on market
Price reductions
Minimum expected profit
Minimum ROI
Maximum renovation budget
Maximum project duration
Available investment capital
Financing requirements
Risk tolerance
Desired exit strategy
Required margin of safety
Investor-specific preferences

The module should identify ambiguous criteria and request clarification when necessary.

Property Discovery Module

The Property Discovery Module searches authorized property data sources for properties matching user-defined investment criteria.

The module should support:

Natural language property searches
Geographic searches
Property characteristic filtering
Price filtering
Investment criteria filtering
Listing status filtering
Price reduction detection
Days-on-market filtering
Distressed-property indicators
Property history
Duplicate property detection
Listing normalization
Saved searches
Watchlists
Automated opportunity monitoring
New property alerts

The module must distinguish between sources that provide authoritative property data and sources that provide supplementary information.

Property Intelligence Module

The Property Intelligence Module creates a comprehensive property profile from available data.

The module should analyze:

Property characteristics
Listing history
Sale history
Price changes
Days on market
Property taxes
HOA information where available
Property type
Square footage
Lot size
Age
Location
Historical transaction information
Available public records
Data inconsistencies
Missing information

The module should produce a property intelligence record with source references, timestamps, confidence levels, and identified data gaps.

Property Condition Intelligence Module

The Property Condition Intelligence Module evaluates available information about the physical condition of a property.

The module should support:

Property photograph analysis
Inspection report analysis
Seller disclosure analysis
Contractor report analysis
Visible deterioration analysis
Deferred maintenance identification
Cosmetic condition analysis
Kitchen condition analysis
Bathroom condition analysis
Flooring analysis
Exterior condition analysis
Landscaping analysis
Roof condition indicators
Water intrusion indicators
Potential structural issue indicators
Potential electrical issue indicators
Potential plumbing issue indicators
Potential HVAC issue indicators
Repair item extraction
Renovation scope generation
Required repair identification
Recommended repair identification
Cosmetic improvement identification
Safety issue identification
Professional inspection warnings
Condition uncertainty analysis

The module should classify properties according to configurable condition categories, including:

Move-in ready
Cosmetic renovation
Moderate rehabilitation
Major rehabilitation
Extensive rehabilitation
High uncertainty
Professional inspection required

The system must clearly distinguish observed conditions from inferred conditions and professionally verified conditions.

Zoning and Highest-and-Best-Use Analysis Module

The Zoning and Highest-and-Best-Use Analysis Module evaluates the legal, physical, and economic potential uses of a property.

The module should analyze available authoritative information concerning:

Zoning classification
Permitted uses
Conditional uses
Setbacks
Lot coverage
Density
Height restrictions
Parking requirements
Minimum lot requirements
Overlay districts
Historic restrictions
Environmental restrictions
Flood-related requirements
Subdivision potential
Access requirements
ADU potential
Addition potential
Expansion potential
Conversion potential
Redevelopment potential

The module should compare the existing use with legally and economically viable alternatives.

Potential uses may include:

Renovation and resale
Expansion
Addition
ADU development
Property conversion
Subdivision
Redevelopment
Rental use
Other legally permissible uses

The module must distinguish between confirmed legal uses, potentially permitted uses, unverified possibilities, and prohibited uses.

The module should not treat a speculative zoning or development possibility as established fact.

Comparable Sales Module

The Comparable Sales Module identifies and evaluates recently sold properties that can support property valuation and investment analysis.

The module should evaluate:

Sale date
Geographic proximity
Property type
Square footage
Bedrooms
Bathrooms
Lot size
Age
Condition
Renovation level
Neighborhood characteristics
Property features
Market segment

The module should rank comparable properties according to relevance and exclude materially unsuitable comparables.

The module should support:

Recent sales analysis
Comparable quality scoring
Outlier detection
Comparable adjustments
Active competition analysis
Pending-sale analysis where available
Comparable evidence reporting

Automated Valuation Module

The Automated Valuation Module estimates current market value using available property and comparable-sales information.

The module should provide:

Estimated market value
Estimated value range
Comparable-based valuation
Condition-adjusted valuation
Location-adjusted valuation
Market-trend adjustments
Property-specific adjustments
Valuation assumptions
Valuation confidence
Supporting evidence

The system should avoid presenting an estimated value as a guaranteed market price.

ARV Confidence Engine Module

The ARV Confidence Engine Module estimates the After Repair Value of a property and evaluates the reliability of that estimate.

The module should analyze:

Renovated comparable properties
Recently sold renovated properties
Comparable quality
Renovation assumptions
Market conditions
Property condition
Expected renovation quality
Competitive inventory
Recent price trends
Outlier sales
Data completeness

The module should provide:

Estimated ARV
ARV range
Confidence score
Confidence explanation
ARV dependency analysis
ARV downside analysis
Maximum supportable ARV
Supporting evidence

The system should identify when the projected investment depends on an ARV that exceeds the support provided by comparable sales.

Market Intelligence Module

The Market Intelligence Module evaluates market conditions at relevant geographic and property-type levels.

The module should analyze:

Local market trends
Neighborhood trends
ZIP code trends
Property-type trends
Price appreciation
Price decline
Inventory
Months of supply
Absorption
Days-on-market trends
Price-reduction trends
Buyer demand
Market momentum
Market volatility
Seasonality
Market regime
Market deterioration
Market recovery

The system should support classifications such as:

Strong seller market
Moderate seller market
Balanced market
Moderate buyer market
Strong buyer market
Rapidly deteriorating market
Recovery market

Market analysis should be performed at the most relevant geographic and property-specific level available rather than relying exclusively on broad regional statistics.

Renovation Cost Intelligence Module

The Renovation Cost Intelligence Module estimates the cost of making a property competitive for its intended market and exit strategy.

The module should estimate:

Materials
Labor
Demolition
Disposal
Permits
Inspections
Appliances
Fixtures
Flooring
Painting
Kitchen work
Bathroom work
Roofing
HVAC
Electrical
Plumbing
Landscaping
Exterior work
Cleanup
Contingency

The module should support local cost adjustments and configurable pricing sources.

Every estimate should identify whether the value is:

Verified
Sourced estimate
Historical estimate
AI estimate
User-provided
Unknown

Renovation ROI Module

The Renovation ROI Module evaluates whether proposed improvements create sufficient financial value.

The module should calculate:

Improvement cost
Expected value contribution
Estimated ROI
Cost-to-value ratio
Buyer-demand relevance
Competitive relevance
Over-improvement risk
Under-improvement risk

The module should prioritize improvements based on expected investment value rather than simply recommending the most expensive renovation.

Financial Modeling Module

The Financial Modeling Module calculates the complete economic profile of an investment.

The module should account for:

Purchase price
Acquisition costs
Closing costs
Financing
Interest
Loan fees
Property taxes
Insurance
HOA costs
Utilities
Renovation costs
Renovation contingency
Holding costs
Selling costs
Commissions
Marketing
Staging
Cleanup
Total project cost
Gross profit
Net profit
ROI
Cash-on-cash return where applicable
Break-even price
Required margin

The model should clearly distinguish projected values from actual values.

Maximum Safe Offer Module

The Maximum Safe Offer Module determines the price at which a property remains financially viable under configured investment requirements.

The module should calculate:

Opening offer
Target offer
Maximum allowable purchase price
Maximum safe purchase price
Walk-away price
Required-profit purchase price
Required-ROI purchase price
Risk-adjusted acquisition price

The calculation should incorporate:

Renovation uncertainty
ARV uncertainty
Market direction
Financing costs
Holding costs
Contingency
Required profit
Required ROI
Margin of safety

Saleability Engine Module

The Saleability Engine Module evaluates how likely a completed property is to sell at the projected price and within the projected timeframe.

The module should analyze:

Buyer demand
Inventory
Comparable listings
Competitive pricing
Days on market
Absorption
Price sensitivity
Property features
Renovation quality
Property presentation
Buyer pool
Neighborhood demand
Seasonality
Financing conditions where relevant

The module should produce:

Saleability score
Expected days on market
Saleability confidence
Competitive position
Price sensitivity
Sale-price probability
Time-to-sale scenarios
Saleability improvement recommendations

The module must distinguish between theoretical market value and practical marketability.

Deal Kill Engine Module

The Deal Kill Engine Module actively attempts to disprove the investment thesis.

The module should stress-test:

Purchase price
Current market value
ARV
Comparable sales
Renovation costs
Financing
Holding costs
Sale price
Sale timeline
Market direction
Hidden costs
Property condition
Zoning assumptions
Exit strategy

The module should identify:

Deal-breaking conditions
Weak assumptions
Margin-of-safety failures
Critical dependencies
Downside exposure
Conditions that make the investment unprofitable

The system should be capable of recommending that an investor reject a property.

Scenario Analysis Module

The Scenario Analysis Module evaluates investment outcomes under changing conditions.

The module should support:

Best case
Expected case
Conservative case
Adverse case
Severe downturn
Renovation overrun
ARV decline
Sale-price decline
Extended holding period
Financing-cost changes
Market recovery
User-defined scenarios

Users should be able to modify assumptions using natural language and immediately receive recalculated outcomes.

Exit Strategy Intelligence Module

The Exit Strategy Intelligence Module evaluates available strategies for recovering value from an investment.

Potential strategies include:

Renovate and sell
Sell as-is
Buy and hold
Long-term rental
Short-term rental where legally permitted
Mid-term rental
Delayed sale
Alternative lawful disposition strategies

The module should compare:

Required capital
Renovation requirements
Revenue
Cash flow where applicable
Financing
Holding costs
Timeline
Profit
ROI
Risk
Liquidity
Market exposure
Confidence

The module should monitor changes in market conditions and recommend strategy reassessment when predefined conditions occur.

Project Management Module

The Project Management Module tracks an investment from acquisition through disposition.

The module should support:

Acquisition milestones
Renovation milestones
Project schedules
Task management
Budget tracking
Cost tracking
Timeline tracking
Contractor tasks
Renovation progress
Cost-overrun detection
Schedule-delay detection
Holding-cost impact
Project status

Contractor Intelligence Module

The Contractor Intelligence Module analyzes contractor proposals and project estimates.

The module should support:

Bid analysis
Bid normalization
Scope comparison
Missing-line-item detection
Cost anomaly detection
Timeline comparison
Payment schedule analysis
Contractor estimate risk analysis
Actual-versus-estimated performance tracking where historical data exists

Investment Ranking Module

The Investment Ranking Module ranks properties according to configurable investor objectives.

Ranking factors may include:

Expected profit
ROI
Risk
Market direction
Renovation complexity
ARV confidence
Saleability
Liquidity
Capital requirements
Timeline
Margin of safety
User preferences

The system should explain the factors contributing to each ranking.

Portfolio Intelligence Module

The Portfolio Intelligence Module evaluates multiple investments collectively.

The module should analyze:

Active projects
Capital exposure
Geographic concentration
Market concentration
Project overlap
Liquidity
Portfolio risk
Capital allocation
Downside exposure

The system should identify when multiple projects create excessive exposure to the same market or risk factor.

Deal Pipeline Module

The Deal Pipeline Module manages investment opportunities through defined stages.

Supported stages should include:

Candidate
Analyzed
Offer recommended
Offer submitted
Under contract
Acquired
Renovating
Listed
Sold
Archived

The module should preserve historical analysis as the property progresses through the pipeline.

Data Provenance Module

The Data Provenance Module records the origin and age of information used in investment calculations.

The module should track:

Data source
Source timestamp
Property record
Comparable source
Cost source
Valuation evidence
Market evidence
Calculation inputs
Assumptions
User-provided information
Verification status

The system should clearly distinguish:

Verified information
Sourced information
Estimated information
Assumptions
Predictions
Unknown information

Natural Language What-If Module

The Natural Language What-If Module allows investors to modify the investment model conversationally.

Supported questions should include:

What if I offer $25,000 less?
What if renovation costs $15,000 more?
What if the property sells for $425,000?
What if the market declines 8%?
What if the project takes six additional months?
What if I rent the property instead?
What is the highest price I can pay and still make $50,000?
Which renovation should I eliminate?
What happens if I sell as-is?

The system should explain how each changed assumption affects the investment.

Deal Autopsy Module

The Deal Autopsy Module evaluates completed investments by comparing forecasts with actual results.

The module should compare:

Forecast purchase price versus actual purchase price
Forecast renovation cost versus actual renovation cost
Forecast holding costs versus actual holding costs
Forecast timeline versus actual timeline
Forecast ARV versus actual sale value
Forecast sale price versus actual sale price
Forecast profit versus actual profit
Forecast ROI versus actual ROI

The module should identify:

Forecast errors
Assumption failures
Property condition errors
Renovation estimation errors
ARV errors
Saleability errors
Market forecasting errors
Timeline errors
Financing errors
Exit strategy errors

The module should identify recurring patterns across completed projects and use historical performance to improve future forecasting.

Learning and Calibration Module

The Learning and Calibration Module evaluates the accuracy of DealSignal predictions over time.

The module should track:

ARV accuracy
Renovation estimate accuracy
Sale-price accuracy
Timeline accuracy
Market forecast accuracy
Holding-cost accuracy
Profit forecast accuracy
ROI forecast accuracy
Confidence calibration

The system should be able to identify systematic forecasting errors and improve future estimates without concealing the historical error.

Notification and Monitoring Module

The Notification and Monitoring Module monitors properties, projects, markets, and investment assumptions.

The module should support alerts for:

New matching properties
Price reductions
Comparable sales
Market changes
ARV changes
Renovation cost changes
Budget overruns
Schedule delays
Market deterioration
Exit strategy changes
Deal-risk changes
Watchlist events

Notifications should be configurable by the user.

Optional Plugin Modules

DealSignal should support optional plugins that extend the core specification without requiring vendor-specific dependencies in the core system.

Property Data Plugins

MLS adapters
RESO adapters
IDX adapters
Brokerage data adapters
Public-record adapters
Property tax data
Foreclosure data
Auction data
FSBO data
Property history providers

Geographic and Regulatory Plugins

Zoning databases
GIS systems
Parcel databases
Permit databases
Building-code databases
Flood-zone data
Environmental data
Historic-district data
Municipal planning data

Market Data Plugins

Rental-market data
Market analytics
Economic indicators
Demographic data
Construction activity
Neighborhood development data
Buyer-demand data

Cost Intelligence Plugins

Contractor pricing
Material pricing
Labor pricing
Regional construction costs
Permit fees
Disposal costs
Equipment rental pricing

Financing Plugins

Mortgage data
Hard-money financing
Private lending
Bridge financing
Construction financing
Loan comparison
Interest-rate data

Property Analysis Plugins

Computer vision
Property photograph analysis
Inspection document analysis
Seller disclosure analysis
Floor-plan analysis
Property measurement analysis

Investment Management Plugins

Portfolio management
Accounting
CRM
Project management
Contractor management
Document management
Investor reporting

Notification Plugins

Email
SMS
Push notifications
Webhooks
Calendar integrations
Workflow automation

AI Decision Framework

DealSignal should use a structured decision framework rather than generating unsupported recommendations.

Every investment analysis should evaluate:

Property opportunity
Property condition
Legal and zoning feasibility
Current market value
Comparable sales
ARV
ARV confidence
Renovation scope
Renovation cost
Renovation ROI
Acquisition cost
Financing
Holding costs
Saleability
Market direction
Exit strategies
Downside scenarios
Margin of safety
Deal-kill conditions
Overall investment risk

The system should produce a recommendation such as:

Strong opportunity
Potential opportunity
Requires further investigation
High risk
Do not pursue

Every recommendation should include supporting evidence and identify material assumptions.

Risk and Uncertainty Requirements

DealSignal must not represent uncertain information as established fact.

The system should identify uncertainty involving:

Property condition
Valuation
ARV
Renovation costs
Market direction
Saleability
Timeline
Financing
Zoning
Permits
Exit strategy

When insufficient information exists, the system should state that additional information or professional verification is required.

Human Verification Requirements

DealSignal is an analytical decision-support specification.

The system should recommend professional verification for matters including:

Structural conditions
Electrical systems
Plumbing
HVAC
Roofing
Environmental hazards
Legal title
Zoning
Building codes
Permits
Property boundaries
Financing
Tax obligations
Insurance
Legal compliance

AI analysis must not be presented as a substitute for licensed professional services or authoritative governmental determinations.

Data and Source Requirements

All external property, market, zoning, financial, construction, and regulatory data must be obtained through authorized sources.

Plugins must respect:

Source licensing
API terms
Data-use restrictions
Attribution requirements
Rate limits
Privacy requirements
Copyright requirements
Applicable laws and regulations

DealSignal must not require scraping or unauthorized access to data sources.

Auditability Requirements

Investment calculations should be reproducible from their recorded inputs.

The system should preserve:

Inputs
Assumptions
Data sources
Timestamps
Calculation results
Model versions
User modifications
Scenario changes
Recommendations

The system should make it possible to determine why an investment recommendation changed.

Privacy and Security

DealSignal should protect sensitive investment information.

The system should support:

User-controlled data
Data minimization
Credential isolation
Plugin isolation
Access controls
Audit logs
Secure storage
Configurable retention
User-controlled deletion
Protection of financial information
Protection of property acquisition strategies

Open Source and Vendor Neutrality

The core DealSignal specification should remain independent of any single property listing provider, MLS, IDX platform, brokerage, contractor marketplace, lender, financing provider, AI model, or cloud service.

Implementations may use different providers through optional plugins while maintaining the same core interfaces and analytical requirements.

Success Criteria

A conforming DealSignal implementation should be capable of taking a natural language investment request and progressing through the following workflow:

Discover → Analyze → Assess Condition → Evaluate Zoning → Value → Estimate ARV → Measure Confidence → Estimate Renovation → Calculate Profit → Analyze Saleability → Stress-Test → Challenge the Deal → Evaluate Exit Strategies → Recommend → Monitor → Compare Results → Learn

The objective is not merely to identify properties that appear inexpensive.

The objective is to determine whether a property represents a defensible investment opportunity after accounting for acquisition cost, condition, renovation, market value, ARV uncertainty, saleability, market direction, financing, holding costs, exit strategy, and downside risk.

Specification Branding License (SBL)

Standard

Fully AGPL-3.0+ compliant system
Copyleft enforced for network deployments
Required attribution:
- Roxanne Ardary
- https://www.roxanneardary.com/

Optional

Specification Branding License (SBL)
- Attribution-free commercial deployment
- Pricing based on scale, usage, and deployment scope
- https://roxanneardary.com/dealsignal/

License & Notice Requirements

DealSignal is released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).
By contributing to any Open Arsenal project, you agree that your contributions will also be released under this license.

Please note the following:

All contributions must comply with the AGPL-3.0+ terms.
Under Section 7 of the license, all redistributions, forks, and derivative works must preserve attribution to:
Roxanne Ardary and roxanneardary.com.
DealSignal specifications are free to use with attribution. A Specification Branding License can be negotiated upon request.
The project’s notice.md file tracks attribution requirements and contributor acknowledgments.
Any update that adds new contributors or modifies attribution should also update notice.md.
When submitting a pull request, ensure that any new files maintain the attribution headers where applicable.
Network-deployed versions of this software must also remain fully AGPL-3.0+ compliant, including exposure of source code modifications when applicable under the license.

For full legal details, please refer to the AGPL-3.0+ license and the project’s notice.md file.

Notice – DealSignal

Attribution Requirement: Under Section 7 of the AGPL 3.0+ license, all redistributions, forks, and derivative works, including network-deployed versions of this project, must provide attribution to Roxanne Ardary and roxanneardary.com.

Contributors

This file tracks contributors and their specific contributions to the project.

Roxanne Ardary, roxanneardary.com – August 14, 2026
Created the repository for DealSignal, an AI-powered real estate investment intelligence specification that discovers, evaluates, values, stress-tests, and analyzes residential property investment opportunities.
[Add other contributors here] – [Date]
[Describe contribution in one sentence]

License – DealSignal

This repository is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

Key Points

You are free to use, modify, and distribute the code.
All redistributions, forks, and derivative works or network-deployed versions must also be licensed under AGPL-3.0+ and provide attribution to Roxanne Ardary and roxanneardary.com as required under Section 7 of the license.
The software is provided “as is,” without warranty of any kind.

For the full license text, see GNU AGPL-3.0 License.