Antenna fills the data gap to help understand insects and protect biodiversity by enabling the scale-up of data collection with greater spatial, temporal, and taxonomic coverage than has ever been possible. It is an online platform where entomologists, ecologists, and machine learning (ML) and computer scientists collaborate to build trustworthy datasets by implementing and improving upon ML research designed specifically for real-world applications. Antenna cost-effectively and rapidly classifies a wide range of species in a large number of images, building a rich dataset that grows and updates over time.

Antenna currently focuses on moths but expansions to other insects are planned.

A billion insects for every human at any one time and 10 million insect species on Earth.

These estimates show how challenging it is to collect sufficient data, recognise observed species, and monitor population changes. Insects are key to ecosystems and agriculture, and severely impacted by climate change. Rich, quality data is critical to describing and responding to insect population patterns.

Antenna uses artificial intelligence to automate, accelerate, standardise, and scale up the identification of invertebrates in the wild. It rapidly performs fine-grained species classification and new species discovery using the GBIF and Darwin Core Standards. The resulting research-grade datasets comprise continuously updating information about the location, time, frequency, quantity of species as observed around the world. Our technology is the most convenient and cost-effective way to enable monitoring at scale.