Zillow shows you price. ACREA shows you everything else — solar yield, aquifer depth, soil taxonomy, flood exposure, build cost, and community health. Unified in 30 seconds. Backed by government-grade data.
ACREA is a geospatial property intelligence platform that delivers institutional-grade land analysis — solar yield, water feasibility, soil quality, environmental risk, construction costs, and community health — in a single 30-second report, priced from $9.99.
The same analysis currently costs real estate professionals $19,300–$265,000 through fragmented consultants and takes 3–9 months. ACREA automates it by pulling directly from government-grade data sources (NREL, USGS, USDA, FEMA, EPA) and scoring properties across 47 variables using Bayesian inference.
Revenue comes from three channels: consumer pay-per-report ($9.99–$29.99), agent subscriptions ($49–$199/month), and enterprise data contracts ($500–$25K). The platform targets a $47B PropTech TAM with 80%+ gross margins at scale.
Entity: Jason McKinney (27.5%), Steve Moehl (27.5%), NEXI Ventures (12.5%), with 25% reserved for an executive partner pool and 7.5% for future investors. Phase 1 launch budget: $15K–$35K. Raising $100K–$300K via SAFE note at a $2M cap — enough for launch, first revenue, and 12–18 months of runway.
Zillow is a $10 billion company built on answering one question: What is this property worth? ACREA answers ten. Traditional 6-pillar real estate analysis costs $19,300–$265,000 and takes 3–9 months. ACREA delivers it in 30 seconds for $9.99–$29.99.
Each pillar draws from peer-reviewed government datasets, validated geospatial APIs, and well-established geoscience methodologies. This is not scraped data — it is the same authoritative source material used by environmental consultants, energy engineers, and USDA agronomists.
ACREA integrates the NREL PVWatts v8 API — the National Renewable Energy Laboratory's industry-standard photovoltaic performance calculator, used by utilities, EPCs, and solar developers globally. All irradiance values derive from the NSRDB (National Solar Radiation Database) Typical Meteorological Year 3 (TMY3) datasets, calibrated across 1,020 NSRDB ground stations.
The yield model accounts for the following system loss stack, per NREL's validated 14% default loss assumption:
Tilt angle is optimized to latitude ± 15° depending on seasonal preference, with azimuth defaulting to 180° (true south). Array geometry is inferred from parcel footprint and estimated roof pitch via LIDAR-derived DSM where available.
Output variables delivered per report: annual AC energy output (kWh/yr), capacity factor (%), estimated system cost ($), simple payback period (years), and 25-year NPV at current utility rates indexed to EIA regional averages.
Well feasibility and groundwater assessment draws from the USGS National Water Information System (NWIS) — the most comprehensive water database in the United States, containing records from over 1.9 million sites. Real-time and historical data includes streamflow, groundwater levels, water quality, and atmospheric measurements.
Aquifer transmissivity — the primary parameter for predicting well yield — is computed from the Theis equation:
Where T is transmissivity (m²/day), K is hydraulic conductivity (m/day), and b is saturated aquifer thickness (m). Confined aquifers report storativity (S); unconfined aquifers report specific yield (S_y), typically 0.1–0.3 for unconsolidated sand and gravel.
TDS (mg/L), pH, NO₃⁻ (nitrate, MCL 10 mg/L), As (arsenic, MCL 0.01 mg/L), F⁻ (fluoride, MCL 4.0 mg/L)Flood hazard integrates FEMA National Flood Hazard Layer (NFHL) Zone designations: Zone A (no BFE), AE (base flood elevation established), AH (ponding), AO (sheet flow), V/VE (coastal velocity zone), and Zone X (minimal hazard). Return periods: 100-year flood (1% annual chance exceedance) and 500-year flood (0.2% AEP).
Soil characterization uses the USDA Soil Survey Geographic Database (SSURGO) — the highest-resolution national soil dataset, mapped at 1:24,000 scale (county-level survey). SSURGO serves data through the Soil Data Access (SDA) API, returning map unit-level attributes for any lat/lon intersection.
Soil classification follows the USDA-NRCS taxonomy hierarchy: Order → Suborder → Great Group → Subgroup → Family → Series. ACREA reports at the Family level for practical interpretability, e.g., "Fine-loamy, mixed, superactive, mesic Pachic Arguiudoll."
Key engineering and agricultural parameters returned per map unit:
μm/s, critical for septic system feasibility; PERC rates >1 μm/s generally suitablecm/cm, the plant-available water storage between field capacity and wilting point; >0.15 cm/cm favorable for dryland farmingEnvironmental risk aggregates hazard layers from four distinct authoritative sources into a single composite score, enabling multi-peril comparison without requiring the end-user to interpret each dataset independently.
Wildfire Risk: USFS Wildfire Risk to Potential Structures (WRPS) model, derived from FLAMMAP fire behavior modeling software. WRPS outputs five risk categories based on conditional flame length probability, embers transport distance, and structure ignition vulnerability. Properties in WUI (Wildland-Urban Interface) zones with >85th percentile WRPS score are flagged as High/Very High risk.
Air Quality: EPA Air Quality System (AQS) reports the composite Air Quality Index (AQI) on the 0–500 scale (0–50 Good; 51–100 Moderate; 101–150 USG; 151–200 Unhealthy; >200 Very Unhealthy/Hazardous). Criteria pollutants reported individually:
PM₂.₅ — fine particulate matter ≤2.5 μm, 24-hr NAAQS standard 35 μg/m³PM₁₀ — coarse particulate, 24-hr NAAQS standard 150 μg/m³O₃ — ground-level ozone, 8-hr standard 70 ppbNO₂ — nitrogen dioxide, annual standard 53 ppbSO₂ — sulfur dioxide, 1-hr standard 75 ppbCO — carbon monoxide, 8-hr standard 9 ppmFirst Street Foundation flood, fire, wind, and heat factor scores (1–10 scale) are integrated as supplementary risk quantification, providing property-level climate-adjusted 30-year risk projections not available from static government datasets.
Construction feasibility draws from RSMeans — the industry-standard cost database organized by CSI MasterFormat divisions (Division 01 General Requirements through Division 49 Process Equipment). Regional cost factors (City Cost Indexes, CCI) adjust national averages to the metropolitan statistical area level.
Material cost volatility is tracked via the BLS Producer Price Index for construction inputs, specifically PPI series PCU2361–2369 (residential building contractors) and PCU2362 (nonresidential), updated monthly. This enables ACREA to reflect lumber, steel, and concrete price spikes in real time rather than relying on stale annual cost books.
Community quality is quantified through four independent data streams, each with documented methodology:
The ACREA Score (0–100) is not an average. It is a Bayesian posterior estimate calibrated against 10,000+ historical real-estate transactions, where the prior distribution for each variable is informed by its empirical distribution across comparable property classes.
Each of the 47 variables in the ACREA model is assigned a prior distribution — informed by the empirical distribution of that variable across properties in the same metropolitan statistical area (MSA). This prevents geographic bias; a GHI of 5.5 kWh/m²/day is exceptional in the Pacific Northwest but unremarkable in the Sonoran Desert.
Posterior updating occurs at the variable level: each observed datum shifts the posterior mean proportionally to its likelihood under the pillar-specific sub-model. Pillar sub-scores (each 0–100) are then combined via a learned weight vector:
Weights are fitted via regularized OLS regression on transaction-level outcome data, with L2 regularization to prevent overfitting on thin data markets. The output reports:
Every ACREA report includes a variable-level attribution table showing exactly which of the 47 inputs drove the score up or down, with contribution expressed in score-points. This is the "show your work" that domain experts demand — and that Zillow's Zestimate famously refuses to provide.
A lean, API-orchestrated scoring engine built on commodity cloud infrastructure. No proprietary data moats — just superior aggregation, normalization, and interpretation logic sitting on top of authoritative public sources.
Detailed breakdown of every API and data source ACREA needs — from free government feeds wired Day 1 to paid commercial providers and the MLS reality check.
| Data Source | What It Provides | Pillar | Cost |
|---|---|---|---|
| NREL PVWatts v8 API | Solar irradiance, TMY3 data, yield modeling, system loss stack | Solar | FREE |
| USGS NWIS API | Well data, aquifer depth, streamflow, groundwater levels, water quality | Water | FREE |
| USDA SSURGO (SDA API) | Soil taxonomy, Ksat, AWC, drainage class, LCC, shrink-swell | Soil | FREE |
| EPA AirNow + AQS API | Real-time + historical AQI, PM₂.₅, PM₁₀, O₃, NO₂, SO₂, CO | Environment | FREE |
| FEMA NFHL API | Flood zone classification, BFE, 100yr/500yr AEP boundaries | Risk | FREE |
| USFS Wildfire Risk API | WRPS score, WUI classification, FLAMMAP fire behavior modeling | Risk | FREE |
| Sentinel-2 (Copernicus) | Satellite imagery, NDVI vegetation index, land cover classification | Soil | FREE |
| Census ACS 5-Year API | MHI, demographics, commute patterns, educational attainment | Community | FREE |
| FRED (St. Louis Fed) | Mortgage rates, FHFA housing price indices, economic indicators | Property | FREE |
| OpenStreetMap / Overpass | Walkability, POI density, road networks, transit access | Community | FREE |
| Provider | What You Get | Monthly Cost | Annual Cost |
|---|---|---|---|
| Trestle / CoreLogic (10 MLSs) | Property listings, comps, ownership history, tax records | $1,000–$5,000 | $12,000–$60,000 |
| ATTOM Data Solutions | Property details, foreclosures, liens, historical sales | $500–$1,500 | $6,000–$18,000 |
| HouseCanary AVM | Automated Valuation Model, property-level price forecasts | $199 + API calls | $2,400–$10,000 |
| GreatSchools API | School ratings, district data, test scores, 3 sub-ratings | Custom | $10,000–$50,000 |
| SpotCrime / CrimeGrade | Crime index by address, trend data, incident categories | $250–$500 | $3,000–$6,000 |
| Walk Score API | Walk, Transit, and Bike scores by lat/lon | $149–$499 | $1,800–$6,000 |
| First Street Foundation | Flood, fire, wind, heat factor scores (30-yr climate-adjusted) | $500–$2,000 | $6,000–$24,000 |
| RSMeans + BLS Construction | Regional build cost per sq ft, labor rates, CCI adjustments | Varies | $2,000–$10,000 |
| Total Data Budget | Full commercial provider coverage | $1,950–$9,649 | $43,200–$174,000 |
There are 580 independent MLSs in the United States — each controlled by local REALTOR associations with their own rules, fees, and data licensing terms. ACREA cannot pull MLS data without either (a) obtaining a broker license in each state, or (b) partnering with licensed broker-dealers. Expect $50,000–$150,000 in legal and BD spend in Year 1 to unlock MLS access in 3–5 target metro markets. Start with Jason's Las Vegas network and Steve's PNW network as the initial broker partnerships.
Three distinct revenue channels: consumer pay-per-report, agent subscriptions for recurring MRR, and enterprise data contracts for large-ticket deals.
Six-week sprint from current state to paid revenue. Three phases, each building on the last.
Four distinct market segments, each with different buying triggers, price sensitivity, and distribution channels. Phase-gated rollout maximizes capital efficiency — start where we have warm networks, expand into higher-value verticals.
Current architecture is lean and deployable. Required additions are all commodity infrastructure — nothing exotic, nothing expensive.
Total capital required: $100K–$300K across two phases. Phase 1 gets us to first revenue in under 6 weeks. Phase 2 activates agent networks and enterprise channels. The platform becomes self-sustaining at ~$20K MRR — no follow-on round needed.
ACREA is structured as a standalone Delaware C-Corp, owned by NEXI. Clean capitalization table designed for institutional investment.