❤️ Relatable
I’ve been farming this land going on sixteen years. You’d think I’d have a better handle on it by now. But truth is, every year feels like a new set of blind guesses. One year it’s too much nitrogen, the next it’s a cover crop that never takes. They sell it like science, but it feels like gambling.
I’ve tried the sensors, the dashboards, the latest regen recs. But I’m still throwing darts. Because none of it explains why things happen the way they do. The fields next door rot out, but ours stay dry. One year, our compost works wonders. The next, the same blend turns sour. And no one can tell me why.
Everyone I talk to has a new app, a new system, a new “miracle microbe.” They chart the inputs and outputs like it’s a machine. But the land doesn’t care about their metrics. It responds to things they’re not even measuring—how long we’ve been growing here, who’s buried in this soil, what we’ve forgotten to listen for.
I’ve been told to aim for yield, for profit, for carbon drawdown, for certification. But none of it explains how my great-grandfather knew what to plant and when, without a single sensor in the ground. None of it teaches me what happens between the soil and the story it holds.
What I’ve needed isn’t another fix. It’s a way to make sense of the contradictions. Why this field turns despite the right numbers. Why that low corner keeps bouncing back even when neglected. Why I trust one patch and not another.
Soil Lover doesn’t give me answers. It gives me reflection. It doesn’t simplify the mess—I’ve had enough of simple. It helps me hold the complexity long enough to start recognizing the patterns inside it.
And that’s the first time I’ve felt like this land and I are speaking the same language.
📘 Professors
Soil Lover: A Living System for Insight, Not Just Optimization
We don’t extract answers from data. We grow them.
What We Do
Soil Lover isn’t another sensor or analytics tool. It’s a new class of decision-making system. One that respects data as a living field, not a static dataset. Through a process called field collapse, users apply intentional pressure using sliders to reveal how attributes behave in relation to one another—within each sample, not just across them.
We don’t track values. We trace relationships. Not “how much nitrogen is present,” but “how nitrogen reshapes carbon drawdown when moisture or microbial activity shifts.” The sliders allow users to interactively uncover and navigate those multi-attribute relationships. It’s like tuning a living instrument—each motion triggers a cascade, a rebalancing, a new set of tradeoffs.
Why It Matters
Most tools today chase peaks. They optimize. They collapse complexity too early, chasing a single solution. But real systems don’t work like that. They’re alive. They’re adaptive. Even success must be managed.
We don’t hop from peak to peak. We walk the field as it grows, shifts, and breathes.
With Soil Lover, even a failing patch of land becomes legible. We ask: what is it choosing to do under pressure? What priorities is it protecting? This isn’t failure—it’s a system trying to balance. We help it reprioritize. And we help thriving zones sacrifice strategically before they collapse.
This is dynamic, field-aware modeling. Like a farmer walking his land, sensing tension in the soil—but now with a tool that mirrors that intuition at scale.
How We Stand Apart
Other tools give snapshots. We give navigation.
- Multidimensional Field Modeling: We model depth, not just surface metrics. Soil is layered, alive, and historic. So is our data.
- Relational Tuning Within Samples: Instead of predicting outcomes from inputs, we reveal how inputs modify one another in context.
- Emotional Intelligence in the System: We treat bias, tension, and value tradeoffs as signal, not noise.
- Universality Across Soil Types: Our system works anywhere—arid, tropical, temperate—because it listens to relationships, not static rules.
- Living, Evolving Answers: We don’t give you a solution. We give you a space to stay with the question.
The data already knows what it wants. Soil Lover just helps it speak.
Why Professors Should Care
You’re not in the business of prescribing simple answers. You’re guiding systems through complexity. Soil Lover is a collaborator in that journey—a lens that reveals, a compass that adapts.
Use it to:
- Fold into grant-funded research on soil, systems, resilience, or AI
- Prototype with students in modeling, HCI, or data design
- Extend lab capabilities into intuition-driven, real-time simulation
We’re not asking you to change your mission. We’re offering you a way to see it more clearly.
Invitation
We’re seeking academic collaborators, not funders. Partners who see bias not as error, but as energy. If you’re ready to help fields speak, we’re ready to listen.
What if the answer lived, just like the microbes? What if your process was alive—and ready to talk back?
Are You Looking the Wrong Way?
Everyone’s staring up. Carbon clouds. Melting ice. Climate dashboards. We’re told the answers are above us—in the air, the atmosphere, the emissions.
But while we’ve been looking up, the collapse has been happening below.
Soil is the real frontier of survival. And right now, it’s being strip-mined of the only thing that ever made it work: connection.
Soil Lover starts by looking down—into the living, intelligent microbial networks beneath our feet—and asking what would happen if we actually listened.
What Is Soil Lover?
Soil Lover is a visualization and interpretive support tool for regenerative land use. But more than that, it’s a way of seeing.
It doesn’t just show you what’s in the ground. It shows you how the ground is responding to you.
By combining empirical data (carbon levels, biodiversity, water retention) with community stories, values, and even cultural memory, Soil Lover creates a reflective interface for understanding land health—not as a set of metrics, but as a living relationship.
It maps intentions, pressures, and feedback loops. It reveals blind spots. It lets the land speak back.
And it does all this not with complex hardware or expensive field equipment—but with a slider-based interface anyone can use.
Simple. Dirty. And brilliant.
Who It’s For
Soil Lover is designed for:
- Farmers and land stewards dealing with endless “solutions” that never address root problems
- Policymakers and planners trying to balance ecological priorities with economic pressures
- Indigenous and ancestral communities reclaiming land narratives across generations
- Climate innovators who know dashboards aren’t enough without grounded context
- Teachers and students exploring land not as a resource, but as a partner
- Everyday people who want to understand why the ground beneath them feels… off
Why Now?
Because we’re past the tipping point—and we’re still asking the wrong questions.
📉 1/3 of the world’s topsoil is already degraded
🔥 Up to 70% of soil carbon loss is due to human intervention
💧 Water retention has dropped by 50% in some monoculture zones
🌽 Global crop diversity has declined by 75% over the last century
And yet every year, billions of dollars are spent on quick fixes, magic seeds, and market dashboards that ignore the web of life below.
Meanwhile, the microbial world—the very system designed to heal, recycle, and grow life—is screaming into the void.
Soil Lover listens. And helps you respond.
The Microbial Truth
Microbes don’t want to fight us. They want to support us. That’s what they’ve always done.
When allowed, they build the networks that feed forests, purify water, stabilize climates, and regenerate barren ground. When ignored, they collapse.
Soil Lover doesn’t engineer them. It cooperates.
It helps us remember that resilience isn’t a war to win. It’s a web to repair.
Let’s stop reacting to symptoms and start restoring systems.
Soil Lover sees the ground differently.
Now you can, too.
Investors
A New St🌱 A New Standard for Grounded Intelligence (With Metrics) 🦠
Soil Lover is interpretive infrastructure for living systems. It doesn’t just show where problems are—it reveals how life is responding, adapting, and healing.
This is not just regenerative land tech. This is a microbial companion layer—a lens for listening to the networks that stabilize ecosystems, purify water, and generate biodiversity.
| Metric | Value |
|---|---|
| Global regenerative agriculture market | $38B, growing at 12% CAGR |
| Smallholder/remote sensing | $5B within the next 3 years |
| SaaS pricing | $2,500/yr per community or field-user |
| NGO/government pricing | $80–150K/yr per deployment |
| 18-month ARR goal | $1.8M (starting from 50 pilot clients) |
| Gross margin | 80–85% (SaaS-native, browser-based) |
| Deployment cost | <$5K per client (no hardware needed) |
| Breakeven target | Q2 2027 at 700 users |
📈 Why Now
- Climate instability is scaling faster than top-down data can adapt
→ $60B global loss in avoidable ecosystem collapse. - SaaS demand for interpretability is rising
→ 30% of funding now tied to community consent & transparency. - Cost of dashboards is outpacing insight
→ Our browser-native tools run faster and cheaper than multisensor platforms.
🔄 Go-To-Market Opportunities (Years 1–5)
Year 1: $2.5M Regenerative SaaS Deployment
• Launch browser-based platform across 50+ clients at $2.5K–$5K/year
Year 2: $5–8M NGO + Policy Expansion
• Partner with NGOs & community labs for scalable, interpretable dashboards
• Deploy multi-field toolkits for consent-based data gathering
Year 3: $10–15M Ecosystem Licensing
• Plug Soil Lover into national/regional land restoration strategies (education, conservation, rewilding)
Year 4–5: $20M+ Semantic Field Infrastructure
• Embed Soil Lover into UX of Earth observation systems
• Modular integration with digital twin visualizations and predictive ecology engines
🧬 Our Advantage
- Filed IP for microbial field interpretation, layered data indexing, and narrative growth logic
- Browser-native + data-flexible — no sensors, no deployment delays
- Custom field companion agents that visualize growth, strain, and microbial response
- Interpretable pattern layer that works as fast as the land changes
🚜 Financials & AI R&D
- $1.25M SAFE or equity round to seed full 2025 pilot rollout
- Path to $3M–$5M ARR by mid-2027
- 1.5x growth stack – $500K pilot → $2M ARR via 3–4 channel expansions
- $300K R&D – visualization, microbial input mapping, UX adaptations
- $200K pilots + $100K team scale-up
- 3–4 pilots signed from soil labs, rewilding zones, and biodiversity field networks
🌎 Vision
At scale, Soil Lover becomes the map beneath the map.
By 2028, we target $15–20M ARR with >85% margins—delivering not just metrics, but meaning, through a grounded intelligence layer.
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Patent
Soil Regeneration Interface via Adaptive Bias Slider Manipulation
(Soil Lover)
ABSTRACT
An interpretive visualization system for land and soil regeneration, using ████████████████ to reflect user-valued priorities across ecological, cultural, and economic dimensions. Integrates empirical data with subjective narratives and outputs layered soil visualizations.
CROSS-REFERENCE TO RELATED APPLICATIONS
█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████
TECHNICAL FIELD
The invention relates to the adaptive visualization and interpretation of environmental transformation systems. It is particularly focused on integrating soil health data, community values, and regenerative practices using ███████████████████████████████████████████████ to align intentions, interventions, and outcomes. These fields may be adjusted manually or annotated for community input, enabling interpretive scenes to be constructed collaboratively, in real-time or asynchronously.
BACKGROUND
Current soil dashboards aggregate and display numeric data, but do not allow for interpretive modeling, ███████████████████████████████████████████████████. They fail to integrate social, emotional, or philosophical █████████████████████████████████████ land-based interventions. These systems lack the capability to blend scientific input with ██████████████████████████████████████████████████████████████████████████████. The absence of intergenerational or cultural contrast in model views further restricts inclusive regenerative planning.
DISTINCTION FROM CURRENT TECHNOLOGIES
Existing dashboards may represent basic soil conditions, but lack ██████████████████████████████ tension recognition, or community narrative integration. Tools that do support scenario building often require deep agronomic expertise or favor one epistemic frame (e.g., scientific over ancestral). They rarely offer ███████████████████████████████████████████████████████████████████.
This invention introduces a hybrid framework combining lab data, ████████████████████████████████████████████████████████. It enables reflective, participatory modeling grounded in cultural nuance and scientific accuracy. ███████████████████████████████████████████████████████████████████████████████, memory mapping, or visioning processes across stakeholder types.
SUMMARY OF THE INVENTION
Standard methods overlook the latent complexity of the microbial field—a multiverse of interwoven ███████████████████choices that, under the pressure of necessity and entropy, repeatedly collapse into singular soil states ████████████████████████████████████████████████. This invention constructs a manipulable interface that allows ███████████████████████████████████████████, rendering locations observable and actionable, and revealing each soil state’s proximity to user-specified goals, thus enabling informed choices with minimal trade-offs—in an elegant and transparent manner.
The system comprises:
███████████████████████████████████████████████████████████████████████████████████████████████Visual overlay tools to show narrative contradictions or synergy (see FIG. 2)███████████████████████████████████████████████████████████████████████████████████AI for flagging interpretive blind spots or suggesting novel framings- Optional field/lab synthesis linkages for empirical cross-verification
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1██████████████████████████████████████████████ biodiversity, spiritual memory, and economic viability.
FIG. 2: Interpretive overlay contrasting regions with distinct value emphases and related suggestions or conflicts.
DETAILED DESCRIPTION
███████████████Regenerative Value- Ecological Resilience
- Cultural Preservation
- Economic Flexibility
- Time Horizon
Data Types:
- Carbon levels
- Water retention
- Crop diversity
- Local interviews
- Spiritual site markings
██████████████████████████████████████████████████████████████████████████████████████Community Integration:
- Users can annotate fields
- Annotations can be weighted and tagged
- Upvoting and generational contrast supported
Microbial Integration:
- The system supports the modeling and seeding of microbial profiles into land or water systems.
- Microbe types and balances can be derived from slider configurations and applied to hydration paths, root interaction layers, or decomposer webs.
- Users may simulate or annotate microbial layering in irrigation systems to encourage resilience, decomposition, or water purification.
Use Cases:
- Land-use mediation
- Policy planning
- Indigenous land recovery
- Intercultural agricultural design
The system may output visualizations, soil health profiles, or printable microbial remediation plans derived from adaptive bias inputs. The system optionally exposes outputs via API endpoints for integration with other applications, dashboards, or workflow tools.
USE OF AI
AI serves as both translator and pattern discoverer. It can:
█████████████████████████████████████████████████████████████████████████Identify neglected traits (e.g., oral memory, water ancestry)- Learn from adjacent land systems or legacy archives
CONSIDERATION OF ETHICAL AND CONTEXTUAL FACTORS
All data layers and interpretive frames are designed for transparency and collaboration. The system supports framing variance (e.g., Permaculture vs. Agroecology vs. Ancestral Stewardship). Safety constraints, bias disclosure, and interpretive accountability protocols are provided.
CLAIMS
- A system comprising:
███████████████████████████████████████████████████████████████████████████████████████████████████an integrated framework for scientific data, cultural narratives, and user-weighted values; and- a visualization layer for comparing soil states across interpretive contexts.
██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████The system of claim 1, wherein the visualization layer identifies alignment or contradiction in user-driven land-use preferences.- The system of claim 1, further comprising a community engagement tool that reveals and visualizes diverse stakeholder priorities and interpretive tensions.
████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████FIGURES & ILLUSTRATIONS
FIGURE 1: ██████████████████████████
FIGURE 2: Overlay ██████████████ Example
U.S. Provisional Patent Application No. 63/823,782, filed June 14, 2025