Vermont Patent of the Month – January 2026

Introduction and Award Recognition

The landscape of American innovation is continuously reshaping itself, driven by the integration of computational intelligence into traditionally analog disciplines. At the forefront of this transformation is US Patent 12,518,067, formally titled “System and method for generating a landscape design.” This intellectual property, filed on July 5, 2023, and officially granted by the United States Patent and Trademark Office (USPTO) on January 6, 2026, represents a watershed moment in the digitization of environmental planning. The patent lists inventors Julie Moir Messervy, David Rose, and Kyle Scharpf, and is assigned to Home Outside, Inc., a company headquartered in Vermont.

In a prestigious acknowledgment of its technological significance, Patent 12,518,067 was recently awarded the Vermont Patent of the Month. This accolade distinguishes the invention not merely for its novelty, but for its disruptive potential within the broader technology sector. The selection process for this award was unique and rigorous; rather than relying solely on subjective human review, the selection committee employed advanced Artificial Intelligence technology to screen, analyze, and benchmark over 1,000 potential patents filed within the jurisdiction. The AI-driven selection algorithms prioritized this invention based on a complex matrix of innovation metrics, identifying it as a standout outlier in a field crowded with incremental improvements. The system flagged the patent for its unique combination of algorithmic complexity and tangible utility, separating it from the theoretical or purely abstract filings that often dominate patent registries.

The selection of Patent 12,518,067 as the Vermont Patent of the Month was predicated primarily on its profound real-world impact. While many patents remain confined to theoretical applications or niche industrial processes, this invention directly addresses a pervasive gap in the property development, environmental sustainability, and consumer software markets: the democratization of professional-grade landscape analysis. The AI selection engine identified this patent due to its introduction of a novel “Scoring Engine”—a technological component that moves beyond mere visualization to provide quantifiable, objective metrics for landscape quality, sustainability, and property value enhancement. By integrating a “calculator engine” and a “design engine” with this scoring capability, the invention empowers users—ranging from individual homeowners to municipal planners—to optimize outdoor spaces for specific outcomes, such as carbon sequestration, water conservation, and aesthetic coherence. This transition from subjective design to objective, data-driven spatial scoring represents a critical leap forward, positioning the technology as a superior solution in a market saturated with purely cosmetic visualization tools.

The following report provides an exhaustive analysis of this invention, benchmarking it against competitors, forecasting its market trajectory, and detailing the specific R&D tax credit implications for the development of such sophisticated software systems.

Technical Architecture and Innovation Analysis

The Core Problem: Subjectivity in Spatial Design

To understand the magnitude of the innovation described in Patent 12,518,067, one must first analyze the historical limitations of the field. Historically, landscape design has been bifurcated into two distinct and non-overlapping domains: high-end, professional landscape architecture, which utilizes complex Computer-Aided Design (CAD) and Building Information Modeling (BIM) tools; and the consumer or “Do-It-Yourself” (DIY) market, which relies on simplified “drag-and-drop” visualizers or manual sketching.

Both approaches suffer from a fundamental limitation: the lack of real-time, objective feedback regarding the quality and performance of the design. A homeowner or a novice designer might place a tree or a hardscape element in a digital plan, but traditional software does not inform them whether that placement optimizes shade for energy efficiency, interferes with local biodiversity corridors, or meets specific impervious surface ratio requirements. The process remains largely subjective, reliant on the user’s inherent knowledge, which is often limited or outdated. Professional tools calculate areas but do not judge “goodness”; consumer tools visualize “looks” but ignore physics and ecology. Patent 12,518,067 solves this by embedding an “expert system” directly into the design workflow, effectively digitizing the judgment of a master landscape architect.

The Solution: The Tripartite Engine Architecture

The innovation described in Patent 12,518,067 is built upon a sophisticated tripartite architecture comprising three interacting software components: the Design Engine, the Calculator Engine, and the Scoring Engine. This modular architecture allows for a seamless flow of data between user input, mathematical computation, and normative evaluation.

The Design Engine

The Design Engine serves as the user interface and the spatial manipulation environment. It allows for the retrieval of landscape data—such as satellite imagery, property lines, and topographical maps—from online databases. This creates a “digital twin” of the physical property. Unlike standard drawing tools, this engine is context-aware. It understands that the canvas is not merely white space but a geolocated plot of land with specific climate zones (USDA Hardiness Zones), sun exposure vectors, and soil types. It facilitates the placement of design elements, but it does so within a framework that recognizes the geospatial reality of the site.

The Calculator Engine

The Calculator Engine functions as the quantitative backbone of the system. It runs in the background, performing real-time computations based on the elements introduced by the Design Engine. When a user adds a specific plant species or paving material, the Calculator Engine computes relevant metrics. These might include:

• Hydrological Impact: Calculating the run-off coefficient of new surfaces to predict stormwater management needs.
• Carbon Metrics: Estimating the biomass potential and carbon sequestration of proposed planting schedules over time.
• Spatial Analytics: precise calculation of distances, areas, and volumes, but enriched with material-specific metadata (e.g., the cost per square foot of specific pavers, or the water requirements of specific turf types).

The Scoring Engine (The Differentiator)

The Scoring Engine is the defining feature that establishes this patent’s superiority and likely triggered the AI selection algorithms for the Vermont Patent of the Month award. It takes the raw data from the Calculator Engine and compares it against a set of “improvement criteria” or benchmarks. It effectively “grades” the design.

This engine utilizes complex algorithms to assess the delta between the “existing condition” (the property as it stands) and the “proposed design.” It assigns a Landscape Score—a composite metric that simplifies complex ecological and aesthetic variables into an understandable rating. This gamifies the design process, encouraging users to improve their score by making better design choices, such as swapping invasive species for native ones or reducing impermeable concrete in favor of permeable pavers. The patent abstract explicitly mentions “determining property landscape improvements by the scoring engine,” indicating a prescriptive capability that guides the user toward optimization.

Algorithmic “Elimination of Uncertainty”

From a technical standpoint, this system eliminates the uncertainty inherent in landscape planning. In traditional workflows, the impact of a design is often unknown until years after installation (e.g., a tree dies because it was planted in the wrong microclimate, or a drainage system fails during a 10-year storm event). Patent 12,518,067 shifts this validation phase “left,” bringing it into the design process itself. The Scoring Engine provides predictive analytics, alerting the user to potential failures or inefficiencies before a single shovel strikes the ground. This represents a fundamental shift from descriptive design (drawing what is there) to predictive and normative design (drawing what works best).

Competitive Landscape and Benchmarking

To fully understand why Patent 12,518,067 was selected as the Vermont Patent of the Month, it is necessary to benchmark it against the existing competitors in the landscape design software market. The market is currently dominated by three categories of tools: Professional CAD/BIM, Consumer Visualizers, and Generative AI Image Generators. The table below summarizes the key distinctions.

Comparative Analysis Table

Detailed Competitor Analysis

Category 1: Professional CAD & BIM (e.g., Vectorworks Landmark, AutoCAD)

Competitor Profile: Tools like Vectorworks Landmark are the industry standard for landscape architects. They are powerful Building Information Modeling (BIM) systems that integrate with civil engineering workflows. The Limitation: These are fundamentally passive instruments. They draw exactly what the user tells them to draw. While they can calculate areas and volumes with extreme precision, they do not inherently “judge” the design. They rely entirely on the professional expertise of the user to ensure the design is sound. If a user draws a drainage pipe flowing uphill, the software might flag a clash, but it won’t necessarily score the aesthetic or ecological value of the planting plan. Furthermore, they possess high barriers to entry due to steep learning curves and high costs ($153+ entry pricing). The 12,518,067 Advantage: The patent democratizes expertise. By embedding the “Scoring Engine,” it allows a non-expert (or a less experienced professional) to achieve professionally validated results. It bridges the gap between a drawing tool and a consulting service. The technology offers a normative framework that guides the user, making high-quality design accessible to a broader demographic.

Category 2: Consumer Visualizers (e.g., PRO Landscape, RealTime Landscaping)

Competitor Profile: These tools focus on aesthetics and sales. They allow homeowners or small contractors to overlay photos of plants onto pictures of houses to see “how it looks”. The Limitation: They are purely cosmetic (“skin-deep”). They do not account for ecological function, feasibility, or sustainability. A user can create a beautiful image of a tropical garden in a desert climate, and the software will not object. The output is often an unbuildable fantasy because it lacks geospatial precision and horticultural data. The 12,518,067 Advantage: The patent introduces “functional constraints.” The Calculator Engine would immediately flag the tropical garden in a desert as a low-score design due to water usage and plant mortality risk. It prioritizes viability over virtuality. The patent’s reliance on “retrieved landscape data” ensures that the design is grounded in the physical reality of the site, not just a photograph.

Category 3: Generative AI (e.g., DreamzAR, Midjourney)

Competitor Profile: Emerging tools use diffusion models to hallucinate beautiful landscape images from text prompts. The Limitation: These are “dream” tools, not “design” tools. They create pixels, not plans. They cannot generate a shopping list, a construction document, or a sustainability report. The images are often physically impossible (e.g., floating plants, impossible perspectives). Users on forums note that while they spark imagination, the designs look “fake” and lack actionable data. The 12,518,067 Advantage: The patent describes a system rooted in data, not just imagery. It generates a design based on logical rules and retrieved data. It produces actionable, constructible plans rather than just inspiration. The “Scoring Engine” provides a deterministic evaluation of the design, whereas generative AI provides a probabilistic visual output with no functional logic.

Statement of Superiority

The technological superiority of Patent 12,518,067 lies in its normative capability. While competitors are descriptive (showing what the design is) or generative (showing what the design could look like), this invention is prescriptive (showing what the design should be).

By quantifying the “goodness” of a design via the Scoring Engine, the technology introduces a feedback loop that trains the user. This is analogous to how a spell-checker trains a writer or a fitness tracker trains an athlete. Competitor software acts merely as a typewriter; Patent 12,518,067 acts as an editor. This capability is particularly disruptive in an era where climate resilience is becoming a mandatory aspect of property development, moving the industry away from purely aesthetic landscaping toward functional, ecological land management.

Real-World Impact and Future Potentials

The selection of this patent as the Vermont Patent of the Month was driven largely by its potential for immediate and substantial real-world impact. The application of this technology extends far beyond simple garden planning; it touches upon real estate economics, environmental resilience, and municipal governance.

Environmental Resilience and Climate Adaptation

The most significant impact of this technology is its ability to scale “Climate-Smart Landscaping.” Currently, sustainable landscape design is a luxury service provided by niche firms. By automating the calculation of sustainability metrics (the Scoring Engine), this patent makes high-performance landscape design accessible to the mass market.

• Carbon Sequestration: The system can guide millions of homeowners to select trees and shrubs that maximize carbon capture for their specific region.
• Water Conservation: In drought-prone regions, the Calculator Engine can actively penalize water-intensive designs and reward xeriscaping, directly influencing consumer behavior to reduce municipal water loads.
• Biodiversity Support: The Scoring Engine can be tuned to reward the planting of native species that support local pollinators, effectively allowing for the creation of decentralized biodiversity corridors across private properties.

Economic Impact on Real Estate

The “Landscape Score” described in the patent has the potential to become a standardized metric for real estate valuation, similar to a “Walk Score” or an “Energy Star” rating.

• Property Valuation: A property with a verified high “Landscape Score” (indicating low maintenance costs, high water efficiency, and mature canopy coverage) could command a market premium.
• Risk Mitigation: Insurance companies could utilize the Scoring Engine to assess wildfire risk. A landscape design that incorporates fire-breaks and fire-resistant plant species would receive a high score, potentially qualifying the homeowner for lower insurance premiums.

Future Potentials and IoT Integration

Looking forward, this patent creates the foundational logic layer for the “Smart Yard.”

• Augmented Reality (AR): The patent’s logic is perfectly suited for AR applications. Users could view their yard through smart glasses, with the Scoring Engine overlaying real-time metrics on physical plants (e.g., “This tree provides 40% shade coverage – Score: A”).
• IoT Integration: Integration with soil sensors could feed live data into the Calculator Engine, allowing the “Landscape Score” to be dynamic, changing with the seasons and the health of the plants.
• Municipal Permitting: Cities could adopt the software to automate landscape permit reviews, requiring a minimum “Landscape Score” for new developments, thereby streamlining regulatory compliance.

R&D Tax Credit Analysis: Utilizing Swanson Reed

The development of the technology described in Patent 12,518,067—specifically the complex interplay between the Calculator, Design, and Scoring engines—represents a textbook example of “Qualified Research” under the United States Internal Revenue Code (IRC) Section 41. Companies engaging in similar development projects can leverage the Research and Development (R&D) Tax Credit to offset a significant portion of their development costs.

Swanson Reed, a specialized R&D tax advisory firm with a strong presence in Vermont, assists companies in identifying, documenting, and claiming these credits. The following analysis details how a project utilizing this patent technology meets the rigorous Four-Part Test required by the IRS, and how Swanson Reed’s methodology ensures a compliant claim.

The Four-Part Test Analysis

To qualify for the R&D Tax Credit, the activities undertaken to develop the software must satisfy all four parts of the following test.

Part 1: Permitted Purpose

• Requirement: The activity must relate to a new or improved business component (product, process, computer software, technique, formula, or invention) that is held for sale, lease, or license, or used by the taxpayer in their trade or business. The purpose must be to improve functionality, performance, reliability, or quality.
• Application to Patent 12,518,067: The development of the “Home Outside” application and its underlying engines clearly meets this criteria. The business component is the software platform itself. The permitted purpose is to create a new functionality—specifically, the ability to automatically score and validate landscape designs against geospatial data—which did not previously exist in the company’s product line. The goal was to improve the performance of the design process (speed, accuracy) and the quality of the resulting landscape plans.

Part 2: Technological in Nature

• Requirement: The process of experimentation used to discover the information must fundamentally rely on principles of the physical or biological sciences, engineering, or computer science.
• Application to Patent 12,518,067: The development of the Scoring Engine relies heavily on Computer Science and Data Engineering.
• Algorithms: Developers had to architect complex algorithms to interpret 2D spatial data (e.g., the proximity of a tree to a house) and translate that into a quantitative score.
• Database Architecture: The system requires the retrieval and normalization of disparate data sets (satellite imagery, USDA hardiness databases, plant species libraries).
• Computational Logic: The “Calculator Engine” involves coding mathematical models to simulate environmental variables (e.g., shadow casting logic, hydrological runoff coefficients). This is not merely aesthetic work; it is hard engineering of software logic.

Part 3: Elimination of Uncertainty

• Requirement: At the outset of the project, there must be uncertainty regarding the capability or method for developing or improving the business component, or the appropriate design of the business component.
• Application to Patent 12,518,067:
• Methodological Uncertainty: How does one quantify “subjective” design elements? There was no standard algorithm for “scoring” a garden. The team faced uncertainty in determining the correct weighting of variables. For example, how much should “drought tolerance” weigh against “aesthetic color harmony” in the final score?
• Technical Uncertainty: Could the system process high-resolution satellite imagery fast enough to provide a real-time score in a web browser without latency issues? How to accurately map 2D user inputs to 3D geospatial reality?

Part 4: Process of Experimentation

• Requirement: Substantially all (at least 80%) of the activities must constitute elements of a process of experimentation. This involves identifying the uncertainty, identifying one or more alternatives to eliminate that uncertainty, and conducting a process of evaluating those alternatives (e.g., modeling, simulation, trial and error).
• Application to Patent 12,518,067:
• Hypothesis Testing: The development team likely hypothesized that a “rule-based” scoring system would work, tested it, found it too rigid, and then iterated toward a weighted machine-learning or heuristic model.
• Iterative Coding: The backend developers would have written code for the Calculator Engine, tested it against known landscape datasets, found errors (e.g., the system miscalculating shade in winter vs. summer), and re-wrote the code.
• A/B Testing: They likely iterated through various User Interface (UI) designs to see how users interacted with the “Score” and whether it actually drove behavior change, discarding ineffective designs.

How Swanson Reed Helps Claim the Credit

Navigating the complexities of the R&D Tax Credit requires distinct expertise, particularly for software patents where the line between “routine development” and “qualified research” can be blurred. Swanson Reed employs a specialized methodology to maximize the claim while ensuring full compliance.

The “Six-Eye Review” Process

Swanson Reed distinguishes itself with a rigorous quality assurance protocol known as the Six-Eye Review. This ensures that every claim related to technologies like Patent 12,518,067 is vetted from three distinct perspectives:

1. Qualified Engineer/Scientist (Eye Pair 1): A technical expert reviews the patent claims and the software development logs. They understand the difference between standard CRUD (Create, Read, Update, Delete) coding and the innovative algorithmic work required for the “Scoring Engine.” They validate that the “Process of Experimentation” was scientifically valid.
2. Tax Attorney/Specialist (Eye Pair 2): A legal expert reviews the claim to ensure eligibility aligns with current case law and statutory requirements of IRC Section 41. They ensure the “Permitted Purpose” is clearly defined and defensible.
3. CPA/Enrolled Agent (Eye Pair 3): A financial expert reviews the “Qualified Research Expenses” (QREs). They ensure that only eligible costs—such as the wages of the developers, the cost of cloud computing power used for testing, and payments to US-based contractors—are included.

Substantiation and Audit Defense

Lack of documentation is a primary reason for claim denial. Swanson Reed helps companies like Home Outside, Inc. create a “contemporaneous evidentiary trail”. They organize commit logs, Jira tickets, and technical meeting minutes to prove the experimentation occurred. Furthermore, their creditARMOR program provides audit defense, utilizing an AI-driven risk management platform to benchmark the claim against industry standards and defend it if the IRS inquires.

Vermont State Specifics

As a firm with specific Vermont expertise (offices in Williston), Swanson Reed can also assist in claiming the Vermont R&D Tax Credit, which is calculated as a percentage of the federal credit. They facilitate the filing of Form BA-404 and Schedule RD, ensuring that the innovation fostered in Vermont results in maximum capital retention for the company.

Final Thoughts

US Patent 12,518,067 is a landmark achievement in the field of landscape technology. By successfully digitizing the complex, subjective process of landscape design into a scoring-based expert system, Home Outside, Inc. has created a tool with significant commercial and environmental potential. Its recognition as the Vermont Patent of the Month, driven by AI analysis, underscores its technical superiority over existing competitors. Through the strategic application of the R&D Tax Credit, supported by the expertise of Swanson Reed, this innovation can continue to evolve, driving further advancements in the sustainable management of our built environment.