Solutions
Production release: insect.id & mushroom.id
Explore the exciting news and improvements in insect.id and mushroom.id comming out with production release.
Crop.health: curing crops, empowering farmers
Discover our new product for crop disease and pest identification. Intergrate crop.health and identify over 300 crpo diseases with breathtaking accuracy.
Unearthing the Journey: Rock.id API
Discover our journey with rock and mineral identification API. Read about the challenges faced and decisions made throughout the process. It has been a process of discovery and learning. The project is currently on hold but remains open for potential future development. Interested parties can contact the team at support@kindwise.com for access to the internal demo or to share ideas for improvement.
Meet the new Mushroom ID!
The new API can identify 3,100 species of fungi (including lichens and related organisms such as slime molds) and includes enhanced information that has been carefully selected and prepared based on the needs of people interested in mushroom identification.
Do The Different Light Conditions Have An Influence On Plant.Id Identification Accuracy?
Plant.id is an API that identifies plant species and diseases from photos with machine learning. Send us images of your plant and get the possible suggestions with plenty of other information including representative images of the species.
Insect.id API beta release is here!
The new API enables you to identify species of terrestrial invertebrates, including insects and spiders from images using a machine-learning model. It is easy to use and we already love how it works.
Use Plant.Id Demo As An App
The primary purpose of Plant.id is to provide a plant species and diseases identification API. To make it accessible to non-programmers, we created a web demo, which you can try at https://plant.id/ website.
Health Assessment Production Release
Let us introduce you to the first production version of Plant.id Health Assessment. During the last year, we have been collecting feedback on the beta version of our plant disease identification API. Moreover, we have expanded our datasets and deepened our understanding of machine learning-powered plant disease identification.