Agentic land due diligence
infrastructure.

Pestren is an AI-powered land intelligence and geospatial aggregation platform. Our swarm of AI agents queries one parcel or a thousand, gathers and reads physical records and geospatial data per county, reasons privately, suggests action, and cites every claim, in minutes.

Sourced from
USDASSURGOSentinel-2LandsatUSGS 3DEPNASAEPAFEMAUS CensusNRELUSFWSUSFSNOAACalGEMNWIPAD-USESA WorldCoverCounty parcel records
time/eight weeks to minutes cost/$1,000–$6,000 saved scale/one parcel or a thousand
80+ factors
soil, water, yield, legal, UCC, insurance, credit
one call, every claim traced to its source
Why not just ask a general model?

Q“Can I set up a grain farm here?”

Without Pestren
GPT, on its own

With Pestren
01 · The industry problem

The world spends $10 billion a year valuing land, and still gets it wrong.

  • $9.94B spent a year valuing property Real estate valuation services market, 2025
  • $116.4B of US property already distressed MSCI balance of distress, Q1 2025 · up 23% year on year
  • $10–20K diligence on one complex parcel Buyer pays up front, and forfeits it if the deal dies
What the market sells Diligence on the one you chose
  • Legal · Financial · Technical · Environmental · Market
Every segment of the category begins after the parcel is picked and the records are gathered. It is priced per property, so it can only run on one.
What they miss Screening the hundreds you reject
  • Developers · Insurers · Lenders · Carbon buyers
Every one of them still reads, scans, uploads and analyses hundreds of fields themselves, just to find the one worth commissioning a report on. That work is the whole decision, and nobody sells it.

The industry serves the parcel you already picked. Nobody serves the hundreds you had to reject to find it. That is where the decision is actually made.

Sources: MSCI Capital Trends, US Distress Tracker · Research and Markets · CrowdStreet on the acquisition funnel · published buyer-paid diligence schedules

02 · Sectors we power

Built for the people who have to be right about land.

A family grower with half a hectare, an insurer with a book of a thousand addresses, a ministry setting policy for a district. Same evidence, same citations, built into whatever they already use.

You rate a postcode. You pay the claim on a plot.

So you write the risks you should refuse, and lose the ones you should want.

What you can ask for instead
  • Send a list of addresses, get an answer on every one
  • Test a claim against what the satellite saw, on the date it was filed
  • Old industrial ground and contamination, flagged before you quote
  • Re-run the whole book at renewal and see only what changed
  • Count how many policies sit in one flood cell or one fire shed
You ask

“For these 1,200 addresses: which flooded before, and where is my exposure stacked?”

We answer, cited

One row per address, problems ranked first, and the register behind every answer.

Ask it yourself →
Policies that turn on land facts
TitleProperty & hazardEnvironmental liabilityCrop & parametricInherent defectsPolitical riskNative title
36%of transactions need extensive, non-routine title clearanceALTA curative work study ↗
$50K–$10Mcleanup liability when a $2,200 site check misses contaminationUS EPA Brownfields ↗
2 in 3homeowners underinsured for wildfire, typically by 20%Insurance Information Institute ↗
03 · Integrate

Plug into any system.

One layer, four ways in. API, MCP, the platform, or data files, and the API itself is two calls: ask a question across a set of parcels, or fetch the fields behind them.

POST/v1/ask

RETURNS BEST FOR
request.sh
04 · Privacy & security

We cite the public record. Your work on it stays yours.

Every answer names a source you can open yourself. What you asked, which parcels you screened, and the client discussion around them are not part of anyone else's answer. We do not train models on your data, and we contractually prohibit our providers from doing so.

Your data stays yours

We do not train models on your questions, coordinates, uploaded boundaries or documents, we contractually prohibit our providers from doing so, and we never sell them on.

What gets cited is public record

Registers, surveys, and satellite passes: FAO, national agencies, ESA Sentinel, NASA, SoilGrids and live weather. Your own parcels never become a source in anyone else's answer.

Client work stays in your account

The parcels you screen, the reports you assemble, and the discussion around them are visible to your account only.

Access is by key, and revocable

Every call is authenticated with a token you issue and can revoke from your dashboard. Nothing reads without it.

Confidence tiers

Every fact is tagged literature-only, field-verified, or lab-confirmed. You always see which, and what it rests on.

Certification, honestly

We are not audited or certified yet. Independent attestation and a formal data processing agreement come with the enterprise tier. Ask what we can commit to in writing today.

Security questions, or anything you need in writing for a client: core@pestren.com

06 · Vibe check

What's your vibe on ungrounded answers?

Pause and see which vibe matches your energy after knowing about Pestren and share your thoughts.

excited
Pestren
results : excited

07 · FAQ

Questions, answered.

The things partners and growers ask us most, starting with where the intelligence actually comes from.

Pestren runs on an open-source foundation model, trained and grounded on openly available, authoritative datasets. Global layers come from ESA Sentinel (satellite), NASA (weather), and ISRIC SoilGrids (soil), plus specialist references like the Insecticide Resistance Action Committee (IRAC) for resistance management. On top of that we use each region's official land-parcel and crop datasets:
  • Europe: LPIS (Land Parcel Identification System), CAP declarations
  • USA: USDA Cropland Data Layer (CDL)
  • Brazil: CONAB, MapBiomas
  • India: state agriculture departments, ICAR institutes, FASAL outputs, plus PMFBY and the Digital Crop Survey where access permits (both restricted)
  • Australia: ABARES
  • Canada: AAFC Crop Inventory
On top of that public base we layer field data and verification points contributed by our partner FPOs (Farmer Producer Organizations), so answers are checked against the real ground, not just the literature. Every answer names the sources it used.
Weather updates daily, satellite refreshes on its revisit cycle, and risk is scored weekly. Every value carries its own timestamp so you always know how recent it is.
Every fact is tagged with a confidence tier: literature-only, field-verified, or lab-confirmed, so you always see whether it's backed by published sources, ground truth from the field, or lab results.
No. We do not train models on your questions or coordinates, and our providers are contractually prohibited from doing so. Field data contributed through FPO partnerships is used only with consent, to improve verification coverage.
Our vision is simple: any crop, any geography. At launch, Pestren supports farms growing food crops across the United States and India. We're already expanding our coverage and plan to add more countries and continents beginning next quarter.
A free tier plus a metered API, with volume plans for enterprise. Grower access is kept low-friction on purpose.
Platform Sectors Integrate Privacy FAQ Contact
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