Beehive management
with machine learning vision

Modern and ethical beekeeping

Honeybees are cute and fluffy, making up a super-organism that we want to take care of, globally. They are key to natural pollination and our food supply. Hobby beekeeping is a challenging physical labor that requires weekly inspections, but is difficult to automate.

Existing solutions on the market are inadequate because they focus on low-cost temperature and sound sensors that provide insufficient information.

Industrial beekeeping like animal husbandry, often raises ethical questions. We want to avoid unhealthy congestion of multiple colonies in a single container, prevent lowering bee lifespan due to mono-culture fields and mobile beekeeping, stop practice of alcohol washing.

Open-source beekeeping assistance system

Long term vision is a single-colony autonomous robotic beehive, powered by deep reinforcement machine learning, giving advanced monitoring to the beekeeper. All of our code is open-source.

Our goals are to:

  • reduce human inspection labor using robotic automation, reducing induced stress on bees
  • save bee colony from hornet attacks
  • give better insights on colony life by analyzing nursing and field bees demographics
  • analyze brood development and hive resources
  • detect colony diseases from mites (Varroa destructor, Braula coeca, Tropilaelaps clareae, Acarapis woodi, Aethina tumida) and bacterias (Paenibacillus larvae)


  • ✅ Detection counting of bees on a frame photo
  • ✅ Visually manage beehive and its frames within a web app
  • ✅ Upload images of beehive frames
  • ✅ Zoom in and draw on top of the frame photos
  • ✅ Plantnet integration with list of local plants
  • ✅ Weather forecast around apiary
  • ✅ Open GraphQL API


Artjom Kurapov,
Beekeeper, Software Engineer, Founder

See also