Intelligent predictions,
informed decisions
Horticulture's weather-exposed economics, finally met with calibrated intelligence.
Today's tools miss the nights that cost the most.
And when they do fire, they hand back a useless, unreliable risk score — never a dollar figure, never a recommendation. Not one incumbent runs an AI reasoning layer.
of damaging frost nights, missed by climatology-based tools
Harvora backtest · 6 NZ regions
of a region's crop, lost to a single frost event
NZ Winegrowers 2025
A thousand futures.
One call you can trust.
Harvora's prediction engine turns raw atmospheric and field data into calibrated weather and agronomic probabilities — then into block-level, dollar-denominated decisions. An AI reasoning layer plans your season, triages what threatens it, and learns every block with compounding seasonal intelligence.
Highlight your blocks. We do the rest.
Setup is deliberately light. Upon completion, Harvora quickly gathers the data and the engine gets to predicting on your blocks.
From probability to decision
A 1000-sample Monte Carlo engine fuses physics models with machine learning across every block — emitting calibrated probability distributions, not point guesses. Deterministic, auditable, millisecond-fast.
The AI-powered finance layer converts each probability into expected value — dollars per block, per decision — in the language growers, lenders and insurers actually use.
Expected-value thresholds and three-tier decision confidence turn priced risk into a clear call: protect or don't, irrigate or wait — AI reasoning shown, drivers attributed.
Every confirmed outcome banks a dollar-valued decision win, builds the block's track record, and retrains the prediction engine and AI models. Intelligence that compounds, season over season.
Catches 94% of frost nights. Block-level frost probability converted to expected-value thresholds — protect or don't, priced against crop-loss risk. Not a temperature chart, a decision engine.
FAO-56 evapotranspiration bounded by real S-Map soil data. Deficit trajectory tracks independent ERA5-Land reanalysis across 6 NZ regions (root-zone r = 0.805) — irrigation scheduled when your soil actually needs it.
Published Plant & Food Research disease models combined with ensemble weather, producing block-level infection-risk curves growers and industry can interrogate.
Growing-degree-day projections anchored to observed heat accumulation. Harvest windows accurate to ±2 days — labour, packhouse slots, and market timing planned from evidence.
First-class crop-cycle intelligence for potato and open-field tomato. An active crop cycle anchors GDD stage, harvest readiness, irrigation context, disease windows and block economics, with four seven-day blight surfaces running the same 1,000-sample probabilistic contract as the wider platform.
Codling moth, potato tuber moth and tomato-potato psyllid lifecycle timing from crop-specific degree-day models, with uncertainty over biofix, thermal thresholds and forecast weather. Block traps and scouting sharpen the regional signal.
Bee-flyable-hour forecasts (92% accuracy) for bloom and day-ahead warnings that catch 97% of damaging-wind days — notice enough to supplement hives or bring a pick forward.
Finds windows that hold: wind, gust, temperature and a dry margin before and after, checked on the 1-day forecast. Of 335 promised windows across 6 NZ regions, 96.7% stayed genuinely rain-free — a defensible go/no-go on product, labour and compliance.
Proprietary in-field soil moisture and temperature sensing feeding the prediction engine with block-level ground truth — closing the loop between forecast and soil reality.
Not a weather app.
An AI prediction platform.
Harvora's machine-learning prediction engine is calibrated against what actually happens on your blocks. It forecasts frost, disease, water stress and harvest windows as honest probabilities, not vague icons. An AI reasoning layer then turns every prediction into dollars and a decision: what's likely, what it costs, and what's worth doing about it.
A 24-feature AI reasoning layer — built for horticulture
Every AI feature exists because of a Harvora prediction. The discipline is grounding-before-generation: deterministic engines find the signal, the AI puts it into words, and a structured fallback ships if it can't. Agentic tool-calling, retrieval-augmented answers, cross-checked responses on high-stakes questions — all sitting on an audited reliability layer, with you making every call.
Explore the intelligence layer →A prediction-driven calendar. Spray, irrigation, frost, harvest and more, planned ahead — and kept current as each new forecast sharpens the picture.
Every night, Harvora reads each block's trajectory and gathers what builds too slowly to trip an alarm — drifts, accumulating pressure, quiet anomalies — waiting in-app by morning.
The urgent calls, pushed to your phone. The reasoning layer decides what's critical and sends it by SMS and email — AI-driven out of the box, with manual thresholds still there if you want them. Deduped, intelligently bundled and paced around quiet hours and action windows.
An agentic assistant grounded in your blocks, your history, your numbers — down to actual costs synced from Xero. A bounded tool-calling loop that retrieves, reasons and runs what-ifs, powerful enough to act — disciplined enough to never act without you.
The longer you grow with it, the better it knows your land
Most software is the same on day one thousand as it was on day one. Harvora isn't. Every season you farm with it, it remembers — and what it remembers, it turns into sharper predictions, quieter alerts, and advice that sounds less like a tool and more like someone who has walked your rows for years.
Every confirmed frost call, every irrigation, every harvest teaches Harvora how each block actually behaves — where cold air pools, how your soils drain and dry, how heat accumulates row by row.
Briefings arrive tuned to how you farm. Thresholds settle around your risk appetite. The question you were about to ask is already answered, in your numbers, for your blocks.
A track record banked in dollars. A memory of every outcome. Models retrained on your ground truth. The intelligence you build never leaves the orchard — it deepens with it.
Published accuracy.
Every prediction.
When Harvora says 30%, it happens about 30% of the time — and we publish the reliability data to prove it. Every surface ships with a measured accuracy stat on real New Zealand data. Calibrated probabilities are trust infrastructure: the foundation growers, lenders and insurers can build decisions on.
See the full proof →A soil sensor node in every block — ground truth, live
Harvora's own in-field hardware: a self-contained, solar-assisted node with a seven-parameter probe in the root zone, reporting every 15 minutes over WiFi or LoRa. Today the engine forecasts your soil from weather; Soil Scouter lets it measure it — correcting the irrigation model's starting point, feeding the per-block learned models, and providing the real-world labels that unlock the deliberately held-back runoff and infiltration ML.
Volumetric moisture (±2%), soil temperature (±0.5 °C), electrical conductivity, pH and N-P-K from a single RS485 probe at root depth — plus ambient temperature and humidity above the ground.
With a reading in the past 24 hours, measured soil moisture replaces the modelled estimate as the irrigation forecast's starting point — cutting the error that accumulates in evapotranspiration estimates.
Solar-assisted lithium cells, a ~20-second wake cycle every 15 minutes, deep sleep in between. Months of unattended operation in an IP65-sealed enclosure — no wiring in the block.
Readings post over orchard WiFi; where there's no coverage, LoRaWAN carries them out — a single gateway covers roughly 5 km of open farmland.
Frost alone is a five-figure decision — per hectare, per season.
Exposure runs to tens of thousands of dollars a hectare. Harvora prices every risk night in dollars and tells you when protection pays for itself — before you start the wind machine, not after. And with read-only Xero integration, the AI reasons with your actual costs and returns — your dollars, not industry averages.
Damaging frost nights per season, average NZ location
Of frost nights missed by climatology tools
Caught by Harvora at the economic setting