Good plant identification
Quick and easy to use whenever you want to
Useless app
You need to pay to get reminder alert. You loose reminder if you don’t go check your reminder by yourself everyday because it only give you the today or future reminder. No history of reminder. So if you forget to go check you won’t know it’s time to water or fertilize your plants. Plants care given are something false and it doesn’t identify the right plant everytime. Useless app.
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Response from developer
Thank you for your review! If you have any further feedback or need support, we’re available at plantorasupport@gmail.com.
Easy to use
The so quickly identified the plant I like the fact that you get reminders to water, repot etc
Not.
Hit or Miss. Sometimes it gets the identification right. Identified a cucumber as a pumpkin, and a rhododendron as a strawberry tree! Diagnosis of problems is done via generic pictures and questions, not from photos of the affected plant itself, resulting in bad diagnosis. Use at your own risk. Asking Google gets better results.
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Pretty bad
I downloaded the free version to test it. Immediately got an ad for paid. When I declined, ads popped up continuously. It could not identify my plant after 3 tries. Then the scam popped up saying the account is restricted for adult content “click here”. 5 minutes in, I removed this app.
Huh
Pic is taken and nothing happens. No instruction available
Waste of time
It does not diagnose issues and major spam. Very disappointing that it was recommended as a free app
Plants
Love this app. Real free
Nice plant app for beginners
Thanks for sharing the information with your app and I recommend it to gain basic knowledge of your plants
Garbage
This app is useless
Great app
Easy to navigate, everything is in one place, and its accurate! Ads are kinda annoying though…
AVOID
Another app promising and not delivering. The plant disease section involves answering a specific set of questions that may or may not apply to your plant issue. This is done is quiz like faction and leads you to a conclusion in write. The most sited issues … under or over watering…. Yeah right. It promises you for free what others provide thru image assessments. Disappointing. Avoid this frustration that will send you looking for answers elsewhere when you don’t trust the info given here.
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They’re Alive
I love plants but have not had the best luck keeping them alive much less thriving. I’ve either overwatered or underfed them in the past. This takes my guessing out of it and my plants are finally blooming
Very disappointed
I did quite a bit of research to find a good app for plant maintenance and some basic id. I knew what most of my plants were, just wanted some verification. I couldn’t believe how many times the app id’ed wrong and the ads are ridiculous, literally half the time I spent on the app was waiting for ads to pass. It looked like it had potential for decent maintenance management, which is why I gave 3 stars not less.
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Wonderful
Plantdora is a seamless and convenient app that lets you properly identify plants, diagnose their health and give recommendations on how best to take care of them. Loving it so far!
Remove add
Good
Not great
Gave me two incorrect answers and 6 “could not find” for one plant. I will look for a better app.
Adds and Mistakes.
It’s got adds. I’m tired of adds. I really hoped to get a cure to my mammey plant but it can’t even identify it.
Perfect for home gardeners
I’ve stopped guessing how to care for my plants. Plantora gives clear watering and sunlight guidance. Very helpful app!
Beware - Plant care data is inaccurate
I’m providing this as direct product feedback, specifically for the engineering and data teams.
The app has strong potential: clean UX, broad plant coverage, and an accessible free model. However, the current state of plant-care data is deeply concerning and undermines the entire product.
I’ve encountered multiple examples where plant guidance is factually incorrect. One clear example is basil, which was listed as needing watering only twice a month and taking months before harvest. In reality, basil requires frequent watering and can be harvested within weeks. This was not an isolated case—similar inaccuracies appeared across multiple plants.
This creates a serious trust issue.
Your users rely on this app because they lack domain expertise. When the data is wrong, the app doesn’t just fail—it actively causes harm to the user’s plants. At that point, the product becomes a liability rather than a helper.
If AI is being used to generate or augment this data, it must be paired with:
• Expert-reviewed source material
• Validation pipelines (human or rule-based)
• Clear provenance of plant-care recommendations
• Guardrails for high-confidence assertions (watering schedules, harvest timelines, toxicity, etc.)
Accuracy must be treated as a first-class feature, not a “nice to have.” Until the data is reviewed and validated by domain experts, users cannot safely trust the guidance being provided.
I strongly recommend pausing expansion and prioritizing data audit and verification. A smaller set of correct information will always outperform a large set of confidently wrong data.
The app has strong potential: clean UX, broad plant coverage, and an accessible free model. However, the current state of plant-care data is deeply concerning and undermines the entire product.
I’ve encountered multiple examples where plant guidance is factually incorrect. One clear example is basil, which was listed as needing watering only twice a month and taking months before harvest. In reality, basil requires frequent watering and can be harvested within weeks. This was not an isolated case—similar inaccuracies appeared across multiple plants.
This creates a serious trust issue.
Your users rely on this app because they lack domain expertise. When the data is wrong, the app doesn’t just fail—it actively causes harm to the user’s plants. At that point, the product becomes a liability rather than a helper.
If AI is being used to generate or augment this data, it must be paired with:
• Expert-reviewed source material
• Validation pipelines (human or rule-based)
• Clear provenance of plant-care recommendations
• Guardrails for high-confidence assertions (watering schedules, harvest timelines, toxicity, etc.)
Accuracy must be treated as a first-class feature, not a “nice to have.” Until the data is reviewed and validated by domain experts, users cannot safely trust the guidance being provided.
I strongly recommend pausing expansion and prioritizing data audit and verification. A smaller set of correct information will always outperform a large set of confidently wrong data.
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