Understand crop problems
Use photos and field notes to make visible symptoms easier to explain and act on.
Field Intelligence
Keep your farm's memory, understand practical guidance, and make better-informed decisions with FildraAI.
FieldGuide helps you act. FieldState helps your farm remember.
Why this matters
Field decisions happen under pressure: weak signal, changing weather, unclear symptoms, limited money, and real consequences. Farming in the dark (forgetting last season, acting on advice without reasons) is the gap FildraAI is built to close.
Use photos and field notes to make visible symptoms easier to explain and act on.
Save diagnoses, tasks, costs, observations, and follow-ups as a working record.
Connect guidance to crop stage, location, weather pressure, and the farm history already recorded.
Turn daily farm activity into structured notes that are easier to review later.
Let farmers start from voice or plain language when typing is slow or impractical.
Build from crop-specific disease research and show evidence where the product can support it.
Who Fildra is for
FildraAI is shaped for smallholder farmers across Africa and Asia first, then for the people who support them. Every feature is tested against whether it actually helps in the field, not whether it looks good in a dashboard.
Farming maize, rice, vegetables, mixed crops, and livestock on phones with weak signal and limited time. The product is shaped around your reality first.
Running multi-plot operations or remote farms. You need farm memory and accountability that works across workers, seasons, and decisions.
Giving advice that farmers act on. You need explainable, inspectable AI output you can trust before passing it along.
How the system works
Each part of Fildra has a clear job: guide the next decision, preserve the farm record, and explain visual evidence when images are used.
Guides the farmer through the next decision, using the field situation and recorded context.
Keeps the farm memory alive between visits, seasons, tasks, and follow-up questions.
Reads crop images and explains what visual evidence the model noticed.
Crop diagnosis, farm memory, and regional context, connected into one working farm record.
The farm record keeps decisions, open tasks, observations, and follow-ups visible after the first answer is gone.
Why farm memory matters
A one-off answer disappears. A record compounds into practical operating memory for field work.
Farmers should not need to explain the same crop, issue, or treatment history every time.
Open tasks, costs, diagnoses, and observations stay visible until the farm resolves them.
Advice becomes easier to review when the evidence and previous decisions are part of the record.
Built for real farming conditions
Fildra is designed to be readable and useful on a phone first, where most field decisions actually happen.
Field work continues when signal is weak, and the record should still make sense when the user returns.
Fildra shows what it knows, what it used, and where a farmer or agronomist should still verify.
What you get when you join
Joining early interest gives you a real seat at the table while we shape FieldGuide and FieldState for your region, crop, and field reality.
Try FieldGuide and FieldState before public release, and use them on your own farm or with the farmers you work with.
Talk to the people building the product. Tell us what is confusing, what is missing, and what is wrong for your context.
Shape which crops, regions, languages, and decisions we support next. We will credit you, with permission, when your input ships.
Try it now
Start with the practical slice: describe the field problem, get a useful next step, and keep a record the farm can use next time.