Less to carry in your head
You put months into a run, and something still knocks it off course. A missed check. A change nobody wrote down. A problem you wish you’d looked at sooner.
Growgoyle helps you plan the work, see what needs attention and follow through. AI brings photos and crop records together while you’re growing, then helps you work out what to carry into the next run.
Built and used by a commercial Michigan grower. Keep your supported sensors. Start without importing old runs.
01 / Make the work easier to do
Put scouting, defoliation and photos on the crop calendar. Choose the people and days. The assignments become crew work without building a second schedule.
The crew can find assigned work on a phone, log progress and keep moving. You can review completed and missed work instead of chasing an update. Recurring maintenance gets a place in the plan as well.
Actual app recordings using fictional demonstration records. Each clip shows a separate workflow.
The labeled time cut represents twelve minutes of work. The worker logs four finished plants while the timer continues.
02 / Stay on top of the crop in front of you
Use the record while there is still work to do. A concern is more useful when it leads to a check, a person responsible and a result you can come back to.
See today’s work, missed tasks and crop context together. Review what AI brings to your attention. When a check makes sense, turn it into assigned work with the room, crop and supporting context already filled in.
This example starts in the Daily Focus email. The manager reviews the suggested check, chooses a teammate and saves the task.
Take a crop photo on your phone. AI reviews what is visible alongside the available batch context and suggests what deserves a closer look. Inspect it, choose the response and assign a follow-up while you’re still in the room.
The demo spots an uneven canopy row and assigns a tuck-and-recheck. Photo analysis supports your inspection; it cannot confirm every cause or replace testing.
Read a contextual photo assessment →The plan, observation and follow-up stay with the crop. Your team can share the work, and you can see what still needs attention. You remain the grower; the record helps carry the details.
03 / Keep the lesson for the next run
Compare crops at the same stage, even when they’re months apart. Keep photos, completed work, feed records and outcomes together so the next review starts with evidence.
These two demo runs are finished. You can also put an active crop beside an earlier run to review the stages recorded so far.
AI helps connect the recorded differences, results and possible explanations. Choose a useful change, put it on the schedule, and check whether the team carried it out. Review the next result before calling it an improvement.
That is how a lesson stays useful when the next harvest gets busy.
Read a real run analysis →Actual app, fictional crop records. AI reviews the documented interruption alongside other changes and suggests a next-run check.
From a real completed run
The harvest numbers didn’t explain the weak density. The review brought together a recorded dosing interruption, later feed running above the recipe target, rising runoff EC and the finished quality. It gave the operator a wider set of connections to investigate.
The operator had already found the interruption. AI helped organize the rest of the evidence and the overlapping changes. The next plan could include a dosing check, a review of delivered feed and follow-up measurements, while keeping the drying work that went well.
See the completed-run analysis How Growgoyle handles evidence and uncertainty →Condensed from a real completed-run analysis
Cultivar A · first tracked run · 90 plants · 24 lights
Possible contributor, not causal proof. The record documents the interruption, not how much yield it cost.
Editorially condensed; not the in-app report layout. Names and select values changed for privacy. The full report includes score breakdowns, strengths, opportunities, phase analysis, and data-quality notes.
Start with one current batch
Use the 30-day trial to find out whether this fits your working week. You don’t need to recreate six months of history to get started.
Eric can help choose your first workflow. Data migration, training across sites and ongoing implementation are scoped separately. Photo review uses the context you have; completed-run analysis needs a finished crop record.
30 days. No credit card required.
$499/month per active facility after the trial. Unlimited users, rooms and batches. Reasonable-use AI allowance applies.