Prioritize faster
Sort noisy land listings by fit, risk and data quality before spending time on broker calls or local diligence.
FrontierArg turns fragmented land listings, geospatial evidence and market signals into a readable scorecard. Free users see the headline. Paid users unlock the reasoning: risk context, comparable logic, geo trust, fair-value range and the checks behind the number.
A land opportunity is rarely obvious from price and hectares alone. FrontierArg explains why a listing deserves attention, what could be wrong with it, and how strong the evidence is.
Sort noisy land listings by fit, risk and data quality before spending time on broker calls or local diligence.
See which KPI modules drive the result: land quality, water context, access, market signal, legal risk and digital usability.
Paid users get a fair-value range and comparable framing, not a magic number pretending to be a formal appraisal.
Geo trust and confidence labels show when a signal is strong, approximate, source-limited or needs human review.
For paid users, FrontierArg turns an asking price into a market reading: how the USD/ha compares to similar listings, whether the area bucket is credible, and how confident the comparable set is.
A fair-value range is a probabilistic market read. It is designed for shortlisting, negotiation prep and red-flag detection, not as a formal appraisal.
We read total price, hectares and USD/ha, then flag missing, placeholder or extreme values before treating the listing as comparable evidence.
The listing is compared against similar opportunities by region, scale, use case and available source quality. Better comparables mean stronger confidence.
Paid analysis shows whether a listing looks under-market, within range, stretched or too weakly supported to price confidently.
Weights vary by country and data maturity. The customer promise stays the same: every score must be explainable, source-aware and clearly labeled.
Soil aptitude, climate profile, rainfall, temperature and regional productivity context.
Rainfall, climate stress and water-adjacent proxies used as an early screening layer.
Visible red flags such as indigenous-area context, mining overlays, seismic context and other policy layers where available.
Distance and infrastructure context: nearby towns, roads, routes, airports and practical accessibility.
Price per hectare, area bucket, comparable listings and regional market context.
Connectivity and digital-infrastructure indicators where reliable public signals are available.
The tabs are not just categories. They match the values that appear in each country scorecard, plus values with data already available but not yet promoted into the official score.
The current public CampoAR focus. Paid analysis can explain listing quality, price context, geo trust and the due-diligence questions a buyer should ask next.
Some signals are precise, others are regional or source-limited. That is why geo trust and confidence labels are part of the product rather than footnotes.
Argentina is the deepest current paid surface. These values are customer-facing labels; internal weights and source QA can change as calibration improves.
| Scorecard value | What it does | Status | Main sources |
|---|---|---|---|
| composite_score | Main 0-100 score visible on listing cards and detail pages. | Live scorecard | Campo score engine |
| investment_grade | Simple A/B/C/D investment-fit label around the score. | Live scorecard | Campo score engine |
| composite_score_raw | Fine sorting and tie-breaker read behind the rounded score. | Fine detail | Score granularity contract |
| score_soil | Land, soil, climate and productive-fit component. | Live scorecard | GeoINTA, NASA POWER, SMN, MAGyP profile |
| score_water | Water and climate-support component. | Live scorecard | NASA POWER, aridity/water proxies |
| score_legal | Visible legal, territory and hazard risk component. | Live scorecard | INAI, SEGEMAR, INPRES |
| score_infra | Infrastructure and services component. | Live scorecard | OSM, ENARGAS, service-distance context |
| score_mobility | Access, roads, airport and mobility component. | Live scorecard | OSM, route/airport distance stack |
| score_market | Market and agro price-signal component. | Live scorecard | Agroads, ZonaProp, Argenprop, MercadoLibre, MAGyP |
| score_digital | Internet/connectivity component. | Live scorecard | INDEC Censo 2022, ENACOM later |
| raw_val_v8 / basis_v8 | Finer component read for tooltip/AI/analyst explanation. | Fine-detail preview | Component v8 promotion gate |
| detail_read_status | Explains whether fine-detail is ready, geo-capped or partial-risk only. | Fine detail | Fine-detail read contract |
| geo_resolution_level | Tells whether location is source coords, geocoded, locality, department or unresolved. | Live trust label | Source coords, geocoder, admin matching, review queues |
| location_confidence | Numeric confidence supporting geo trust and map visibility. | Live trust label | Geo resolver, source evidence |
| nearest_localidad_nombre / dist_localidad_km | Nearest locality context for access and geo caveats. | Detail value | listing_geo_features, OSM/admin layers |
| frost_days_local | Local frost-day signal for climate/productive caveats. | Detail value | SMN nearest-station match |
| dist_inai_km | Distance to INAI territory context. | Detail value | INAI |
| dist_segemar_km | Distance to mining/geology context. | Detail value | SEGEMAR |
| price_usd / price_per_ha_usd / area_ha | Listing price basis used for market and valuation reads. | Live listing value | Listing sources, parser normalizers |
| pricing_verdict | Under-market, in-range, over-market, suspicious or indicative verdict. | Pro/Fair Value | Valuation RPC, comparable set |
| quality_adjusted_value_usd_ha | Estimated USD/ha offer-value after quality adjustment. | Pro/Fair Value | Valuation RPC |
| fair_low_usd_ha / fair_high_usd_ha | Estimated market range, shown as a band rather than an exact appraisal. | Pro/Fair Value | Asking-price comparables |
| comparable_quality | Quality score for the comparable set. | Pro/Fair Value | Comparable grouping |
| comparison_group | Market group used for price comparison. | Pro/Fair Value | Province, area bin, source market |
| valuation_confidence | High/medium/low confidence label for the price read. | Pro/Fair Value | Geo trust, comparable quality, source coverage |
| regional_productive_profile | Regional productive type, caveats, strengths and buyer hints. | Detail value | Score signals, frost, soil, water, geo trust |
| ENACOM mobile coverage | Connectivity booster when reliable coverage is available. | Pending score use | ENACOM |
| IDECOR OMI anchor | Cordoba market anchor for offer-to-transaction calibration. | Future calibration | IDECOR OMI |
| Catastro evidence | Future/operational location hardening where official evidence supports it. | Pending promotion | Provincial catastro / review queue |
| border / flood / drought / fire risk | Risk layers that can strengthen legal and water reads once validated. | Future score layer | Official risk layers, hydrology, hazard sources |
The same scorecard vocabulary can support Uruguay once source coverage, review workflows and market calibration are strong enough for customer-facing use.
Country-specific official layers and local market behavior matter more than copying Argentina weights.
Uruguay remains readiness-gated. These are the values the country tab would expose when the source and review loop are safe enough.
| Scorecard value | What it does | Status | Main sources |
|---|---|---|---|
| reduced_scope_score / grade | Internal UY fit read without public paid claim. | Internal scorecard | UY internal scorecard |
| listing_integrity_score | Checks title, source identity, price, area and basic listing usability. | Internal scorecard | InfoCasas UY, Farmland UY, CamposOnline UY |
| market_price_signal_score | Reads USD/ha against available UY rural samples. | Internal scorecard | UY listing samples |
| source_richness_score | Scores how much usable source context the listing provides. | Internal scorecard | Source parser QA |
| location_confidence_score | UY geo evidence score; department-only remains weak. | Internal scorecard | DNC/admin evidence, geocoding, review loop |
| direct_coneat_index | Productive land-quality candidate where CONEAT evidence is available. | Pending promotion | CONEAT / UY official context |
| geo_resolution_level / quality_flags | Labels whether the UY score can be trusted at point, locality or department level. | Internal trust label | DNC review, source coords, geocoder |
| water / services / access claims | Useful source claims not yet safe as official score components. | Future score layer | Listing text, official layers later |
Paraguay requires its own lane logic, source policy and official-layer hardening before a paid valuation promise is made.
A market is only promoted when FrontierArg can explain the score, label the evidence and defend the limitations.
Paraguay is deliberately not an Argentina clone. The public tab should explain lane and source readiness before any paid score or valuation claim.
| Scorecard value | What it does | Status | Main sources |
|---|---|---|---|
| internal_score / internal_grade | Current internal PY read, not a public paid score. | Internal scorecard | PY internal scorecard |
| internal_score_v2 / internal_grade_v2 | V2 preview with better lane and source separation. | V2 preview | Campo PY scorecard V2 |
| listing_integrity_score_v2 | Checks source, title, price, area and duplicate risk. | V2 preview | TuLugar, InfoCasas PY, MercadoLibre PY, Clasipar proofs |
| market_price_signal_score_v2 | Reads USD/ha or USD/m2 depending on lane. | V2 preview | PY listing samples |
| location_confidence_score_v2 | Measures geo/admin confidence for city, distrito or source-coordinate evidence. | V2 preview | INE/admin matching, geocoder, source coords |
| source_confidence_score_v2 | Separates reliable sources from thin scraped context. | V2 preview | Source-card QA |
| lane_context_score_v2 | Reads urban-fringe and campos differently. | V2 preview | Lane contract, market_lane |
| environmental_legal_risk_score_v2 | Early environmental/legal risk read; not yet a public claim. | Pending hardening | INFONA, MAG, BHAg candidates |
| price_reference_ratio / percentile / market_bucket | Market-position values behind PY price context. | Internal market read | PY market context |
| border_zone_50km_flag | Border-zone context that may change diligence requirements. | Pending policy read | Admin boundaries / border context |
| MAG / INFONA / BHAg native layers | Future native official backbone before any paid PY valuation. | Future score layer | MAG, INFONA, BHAg |
Chile, southern Brazil and other markets can reuse the explanation framework, but only after source rights, pipeline stability and local risk layers are ready.
FrontierArg sells analysis and navigation, not scraped listings repackaged as certainty.
Future tabs should not imply a live product. They show what must become true before FrontierArg sells scorecards in a new country.
| Candidate value | Why it matters | Status | Example sources |
|---|---|---|---|
| water-rights signal | Critical for Chile and water-sensitive rural land. | Future score layer | DGA / official water registries |
| soil capacity / productive use | Local productive fit without copying Argentina weights. | Future score layer | CIREN, MinAgri, official soil datasets |
| hazard / fire / flood / slope risk | Risk layer for land usability, financing and insurance questions. | Future risk layer | Official hazard services |
| source compliance status | No paid launch if listing rights and source policy are weak. | Launch gate | Source policy, terms, partner paths |
| market calibration anchor | Needed before making credible fair-value claims. | Future calibration | Official anchors, partner transactions, validated comps |
FrontierArg uses AI where it creates leverage: reading unstructured listings, normalizing signals, explaining score drivers and surfacing review questions. The model does not replace source labels, confidence checks or human due diligence.
AI helps extract useful clues from messy titles, descriptions and broker language: water claims, access hints, productive use, location phrases and missing-information warnings.
AI-assisted review helps flag ambiguous locations, homonyms, weak source evidence and cases where a listing should stay locality- or department-level until reviewed.
AI turns raw score components into buyer-readable explanations: what lifted the score, what capped it, which caveats matter and which next questions are sensible.
AI helps frame price signals without overstating them: why a listing appears under-market, stretched, indicative or too weakly supported for strong valuation language.
For paid reports, AI can prepare a structured first draft: strengths, risks, source caveats, valuation context and diligence questions for human review.
AI can help surface suspicious prices, inconsistent area units, duplicate-looking listings, missing source context and unusual combinations that deserve operator attention.
The scorecard is useful because the individual values explain a listing. These are the signals buyers can use to ask better questions before calling a broker, visiting the property or paying for a deeper review.
A score without confidence can mislead. FrontierArg pairs each analysis with labels that tell you how to read the result.
| Label | What it tells you | Why it matters commercially |
|---|---|---|
| Geo trust | Whether the location is source-provided, geocoded, locality-level, department-level or unresolved. | Distance, risk and access metrics are only as strong as the location basis. |
| Source basis | Whether the analysis relies on asking prices, official anchors, partner transactions or mixed evidence. | Buyers can separate market signal from formal valuation certainty. |
| Fair-value confidence | How strong the comparable set and price band are for the listing. | A weak band still helps screening; it should not drive negotiation alone. |
| Review required | Flags that need human review, local diligence or original-source confirmation. | This is where Deal Check becomes more useful than a self-serve score. |
FrontierArg sells analysis, context and navigation. We do not replace a lawyer, notary, agronomist, broker, title search, registry review or on-site inspection.