ListenField connects weather, satellite, field and supply data. Our AI agents show what is happening in your fields and supply chain, and what to do next.
We train and test our models on our own verified data, and we build the AI workflow around your business.
In production since 2017 · Japan · Thailand · Laos · Vietnam · Colombia
Critical Thursday is 38 t over capacity (112%).
Group B ripened early, adding 24 t in 24 hours. With 3 days left, moving its 96 t to Saturday brings Thursday to 262 t and Saturday to 306 t.
Tonnes per day at the plant · capacity per plant spec, plan per contract · today is Monday
Tonnes per day: Mon 284 t (received), Tue 296 t, Wed 312 t, Thu 358 t, Fri 301 t, Sat 210 t, Sun 188 t, Mon 276 t, Tue 290 t, Wed 335 t, Thu 300 t, Fri 270 t, Sat 240 t, Sun 205 t
| Group | Ready to harvest | Status | Field data | Next step |
|---|---|---|---|---|
| Group B | Thu · 96 t ±10 | Critical day | Today 06:10 | Move to Sat |
| Group D | Next Wed · 88 t ±12 | Watch day (105%) | 3 days ago | Review |
| Group C | No forecast | No data | No visit in 8 days | Request a visit |
Why is Thursday over capacity?
Checked 3 sourcesweather · satellite · field reports
Group B ripened faster than expected, adding 24 t to Thursday's forecast in 24 hours. Thursday now totals 358 t from 5 groups, against a capacity of 320 t.
What if we move Group B to Saturday?
Checked 2 sourcesintake plan · plant capacity
Thursday drops to 262 t (82% of capacity) and Saturday rises to 306 t (96%). Next Wednesday stays at 105%, so I'll keep watching Group D.
Which groups have no field data?
Checked 1 sourcefield visit log
Group C has had no field visit in 8 days, so it has no forecast yet. I've drafted a visit request for the field team.
Our own field data, collected and verified since 2017, combined with weather records from 1980 and satellite data. It is the base we use to plan supply-chain production.
ListenField watches your supply network continuously and listens to your business target. It spots problems before they become crises and drafts the work, the actions and the deadlines. We centralize the data and decentralize the action: data preparation and analysis run automatically, and the people in your workflow decide and act.
Some of our customers
Our partners
Every food company makes a promise: the right crop, in the right amount, at the right time. This short film shows how we turn that promise into a plan for every field — and how the plan keeps itself up to date when the weather, the soil or the harvest changes.
One target drives three AI layers. Data preparation and analysis run automatically, and the people in your workflow decide and act.
AI reads 340 fields every day. You see one number: confident or not. Yield models from regional to field-polygon level with risk signals and harvest window alerts 21 days before.
The AI holds the full supply picture. You don't have to. Portfolio-level forecasts across countries, crops, and sourcing zones — connected to your factory planning with shortfall alerts and re-sourcing options.
The agent drafts tasks and schedules; your team approves and sends them. Farmers, agronomists, field operators and machine contractors get their instructions on mobile, and progress is tracked in real time.
Unilever
Partnering with Livelihoods Ventures and Kasetsart University on a Regenerative Rice Project — data and analytics to improve the feedback loop for farmers.
Sun Sweet
Predictable production planning, informed prediction results, and tools to reduce risk including a planting calculator.
Sapporo Beers
Growth monitoring, maturity prediction, and lodging detection — earning positive feedback from both research teams and farmers.
Centralized data. Decentralized action. See how it works on your supply chain.
Request a demoListenField's AI platform combines satellite imagery, climate models, and soil data into a single intelligence layer that monitors your entire supply network continuously. Instead of reacting to shortfalls after they happen, the system detects risk signals early and provides actionable forecasts — so your procurement team can re-source proactively. It has been running inside working food and agriculture supply chains since 2017, across five countries.
We start with a season-ahead outlook. Using seasonal climate forecasts, ListenField gives a first view of supply 3 to 6 months ahead, early enough to plan production, logistics and sourcing. That first view is an outlook, not a final number. As the season progresses and field and satellite data come in, the forecast is updated and becomes more precise, and it is most reliable in the weeks before harvest. Risk signals and harvest window alerts continue throughout the season.
ListenField has production-validated models for sweet corn, barley, potato, vegetables, sugarcane, rice, cassava, and herbs — deployed across Japan, Thailand, Laos, Vietnam, and Colombia. For new crops, the platform can be configured and operational within 30–90 days, depending on data availability and growing cycle. The AI learns from your specific fields and conditions every season. Accuracy varies by crop, region, season and how much field data is available, and we discuss it openly with each customer.
ERP systems like SAP and Oracle focus on factory-side production data — what was ordered, what was produced, what was shipped. ListenField focuses on what is happening in the field before raw materials reach the factory. It ingests environmental data — soil conditions, climate patterns, crop growth stages — and trains AI models to understand how these conditions translate into supply risk, yield variance, and harvest timing. ERP records the past. ListenField predicts the future and links field conditions to factory planning.
Traditional BI tools give you charts and reports, but you have to configure data pipelines yourself, interpret the numbers, and decide what to do. ListenField is different: it builds the entire data pipeline for you — connecting your field data with satellite imagery, weather models, and soil surveys — then learns your specific workflow. Instead of generic dashboards, you get actionable intelligence tailored to each stakeholder: the factory manager sees supply forecasts, the agronomist sees field-level risk alerts, the logistics team sees harvest schedules. Data preparation and analysis run automatically. The agent flags what needs attention and drafts the next action, who it is for and when it is due, and the people in your workflow decide and act.
Trusted by leading food and agriculture companies across five countries. Some of our customers: Sun Sweet (sweet corn, Thailand), Eastern Sugar & Canes (sugarcane, Thailand), Sapporo Beers (barley, Japan), Unilever (regenerative rice), PepsiCo (potato supply chain), Ajinomoto (cassava), Sumitomo Chemical, East West Seeds and VSC Food. Kubota is a strategic investor, and we also work on development programmes with ADB, IFC, JICA and UNDP, including ADB's climate-smart agriculture project in the Greater Mekong Subregion (GMS).